Software Testing Help Archives - Page 3 of 12

Strategies for Testing in AI Applications Best Practices and Key Considerations

Posted on May 18, 2023December 28, 2023 by tbsupadminnxtbackendacc

Artificial Intelligence (AI): Artificial Intelligence (AI) is the latest technology to be leveraged across all industries and domains which are increasingly complex and continuously accessible marketplace, organizations must evolve. It is the ability of machines to perform tasks that usually require human intelligence.

How does Artificial Intelligence work?

AI works by merging big data sets with iterative processing algorithms and with intelligence to learn from features and patterns in the dataset that AI systems Analyze.
Each time an AI system performs a data cycle, it checks and measures its performance and gains additional knowledge.
AI science aims to create computer systems that can simulate human behaviour to solve complex problems using human-like thought processes.
AI systems use different technologies and different methods and processes to achieve this goal.

AI helps to access and manage the computing resources to train, test, and deploy AI algorithms and is playing a essential role in the software industry which also includes software testing. Testing is the basic activity aimed at detecting and solving technical issues in the software source code and assessing the overall product usability, performance, security, and compatibility. It’s not only the main part of quality assurance; it is also an integral part of the software development process.

Since AI has the ability of mimicking human intelligence, the penetration of AI in testing is on the rise.

Evolution of AI in Software Testing

According to the World Quality Report 2019-2020, it is stated that AI-based testing is on the rise, and to make testing smarter, more effective, and more efficient, organizations are adopting AI-based tooling and processes in software testing. Typically, the application of AI in software testing will make the entire testing process faster, clearer, easier, and budgeted. Therefore, AI-based testing will provide a strategic platform where software testers can leverage AI and take the testing process to a new level and thus deliver more quality results to businesses.

The paradigm of software testing has evolved significantly over the past two decades. Right from manual testing to automation testing, where selenium is considered to be one of the finest test automation tools, the testing journey has been quite encouraging. However, in today’s fast-paced IT world, the domain of software testing has to come up with innovative and well-researched testing methodologies.

AI algorithms can completely mimic human intelligence, and ML allows computers to learn automatically without any human intervention. Interestingly, AI and ML involve the development of unique and specific algorithms that can access data learn from that data by extracting patterns to make decisions, and these predictions are to be used in software testing effectively.

Read Also: Personality Analysis of Software Testers A Scientific Approach

Benefits of AI in Software Testing

1. Reduced Test Flakiness
By automating repetitive tasks and using algorithms to detect bugs and issues, AI helps to speed up the testing process and improve the accuracy of results. This means all the software can be tested more efficiently and effectively, saving time and resources while ensuring a higher-quality product.

2. Better Test Coverage
Artificial intelligence has the potential to automate manual tests and identify issues quickly, reducing the time required to detect bugs and errors. By automating testing activities and reducing human error, AI can help you deliver better quality software more quickly.

3. Faster Feedback Time
AI helps in faster detection of bugs in the product. Early detection results in improved product quality since the developers receive faster feedback about the product. Accelerated feedback time also improves developer productivity since issues are reported at a faster pace. The impact of AI-based testing multiplies by a huge margin when the tests are run in Continuous Integration pipeline.

4. Faster Test Script Generation
Codeless AI testing is significantly faster than either manual testing or traditional automated solutions, as testers save time generating code. This allows companies to increase their ability to run tests and deploy more quickly.

What is AI-based Testing?

AI-based testing is a software testing technique in which AI and Machine Learning (ML) algorithms are used to effectively test a software product.

Machine learning is one of the key techniques we use to achieve this. It forms the basis for many AI systems, but not all. AI and machine learning in software testing deliver better and more effective automation, relieving teams of the burden of repeating and refining testing.

Many software testing methods are now powered by Artificial Intelligence .The objective of AI-based testing is to make the testing process smarter and highly effective. With the inclusion of AI and ML in testing, logical reasoning and problem-solving methods can be applied to improve the overall testing process.

Moreover, enterprises are rushing towards tools that can leverage AI and ML algorithms and can be used for testing the software effectively. It has also been seen that businesses get many benefits from AI-based testing as it will enable faster and continuous testing, complete automation without any human intervention.

Read Also: AI and Bots: Are They The Future of Software Testing?

Some of the benefits of leveraging AI in software testing:

1. Visual validation:–

It helps to make sure that all the visual elements are engaging and can function properly. Improved accuracy: with the advent of AI in automation testing, repetitive tasks are handled more effectively and the results are recorded more accurately. AI has pattern recognition and image recognition capabilities that together help to detect visual bugs by performing visual testing on applications. It helps to make sure that all the visual elements are engaging and can function properly.

2. Improved accuracy:–

Through machine learning, AI helps to generate test data where testers can feed the data into an AI machine allowing it to perform various tests at every stage without the need for manual testing hence improving the reliability and security of the software.

In the manual testing method, the chances of human-prone errors are high, especially in situations of repetitive tasks. Automation testing helps in removing these human-prone errors. Thus, AI helps in removing the minute chances of errors and improves the overall accuracy of tests.

3. Better test coverage:–

AI in testing increases the test coverage as it can check the file contents, data tables, memories, and internal program states seamlessly. Saves time, money, and efforts: Software tests need to be repeated whenever there is an instance of change being made in the source code. AI in testing increases the test coverage as it can check the file contents, data tables, memories, and internal program states seamlessly. It also helps to determine if the program works as expected and delivers effective test coverage.

4. Saves time, money, and efforts:-

Software tests need to be repeated whenever there is an instance of change being made in the source code. Manually this becomes time-consuming and takes a lot of effort from testers. But, with AI-driven tests, repetitive tasks are handled properly, quickly, and efficiently.

5. Faster time-to-market:–

AI uses a set of algorithms to analyze software functions and identify errors through automated testing, thus minimizing the headaches of repetitive software testing tasks (such as regression tests), improving accuracy, and accordingly shortening time to market. AI-driven tests support continuous testing, and thus products are released faster which helps businesses go early-to-market.

6. Reduces defects:–

AI-driven tests support continuous testing, and thus products are released faster which helps businesses go early-to-market. AI in testing helps in early and fast bug identification, which ultimately reduces the defects and makes the product bug-free, and reliable for end-users.

What are the 4 main categories of AI-driven testing tools?

1. Differential tools:-

Helps test different versions of similar applications. Carries out a comparison to understand differences, versions overbuilds and learn from classification feedback. Visual: Image-based testing needs visual validation. Differences are classified and application versions over each build are compared in this type of testing.

Tools leveraging AI and ML algorithms aim to proactively and automatically identify code quality issues, regressions, security vulnerabilities, and more. This is done through code scanning, unit test automated creations, and more. If your team lacks skills to address the above objectives or does not have the time to continuously address these tasks, consider some of these options. The outcome will be faster releases, improved quality through fewer escaped defects, and better productivity for developers. Some of the tools under this category are:

Launchable:

Launchable is based on an ML algorithm that predicts the likelihood of failure for each test based on past runs and whenever the source code changes under test. This tool lets the user record the test suite so that tests that are likely to fail are run first. One can choose this tool to run a dynamic subset of tests that are likely to fail, thereby reducing a long-running test suite to a few minutes.

It looks at code automatically upon a code pull request and performs a kind of code impact analysis that adapts to the recent code changes. It then selects only the most relevant subset of your regression suite to save time to approve the code changes and integrate them into the pipeline.

Google OSS-Fuzz:

It is a fuzz testing tool that aims to make common open-source software more secure, stable, and reliable. This tool combines modern fuzzing techniques with scalable and distributed execution. This tool supports C/C++, Rust, Go, and Python code.

Facebook Infer:

Facebook’s Infer project also enables better code quality through its AI algorithm. The AI engine from Facebook can automatically find null pointer exceptions, memory leaks, concurrency race conditions, and more in Android and Java code. Similarly, it can also find the same issues together with wrong coding conventions or unavailable APIs in C, C++, and iOS/Objective C code.

DiffBlue:

DiffBlue connects into your source control repository (Git, Perforce, etc.) and creates a base line of unit testing automatically through AI. Once a regression is found, a flag will be thrown reporting the issue. The motivation for DiffBlue to create their solution was mostly to improve code quality by helping developers who do not like to own test creation.

Read Also: Software Testing Latest Trends & Technology in 2023

2. Visual AI testing tools

Visual testing is a software testing technique in which the look and feel of an application is tested by leveraging image-based learning and screen comparisons. With pattern and image recognition capabilities together, it helps detect visual bugs to test the look and feel of an application.

Visual AI testing tools address the pain of constant changes made to the UI (user Interface) layer together with an ever-growing number of platforms, screen sizes, and configurations that make testing coverage a nightmare for test engineers and developers. With the ever-growing number of platforms that vary in screen sizes and have different configurations, it has become a tedious task for test engineers and developers to effectively test the UI layer.

Also, the UI layer experiences constant changes from time-to-time as businesses wish to provide a better user experience. Therefore, today there is a dire need for visual AI testing tools that effectively test all variations of these UI layers.

Some AI/ML tools that fall into this category are:

Applitools
Percy.io

1. Applitools:

This is an AI-powered visual testing and monitoring platform. This has been named a next-generation test automation platform powered by Visual AI. The major features include Applitools Eyes which helps to increase test coverage and reduce maintenance. The Ultrafast grid helps with cross-browser and cross-device testing and accelerates functional and visual testing by 30 times. This Applitools platform integrates with all modern test frameworks and works with many existing testing tools like Selenium, Appium, Cypress, etc.

2. Percy by BrowserStack:

It is an all-in-one visual review platform that comes with amazing features such as pixel-by-pixel diffs, responsive diffs, and snapshot stabilization. This tool allows cross-browser rendering, high-speed rendering, and has parallelization capabilities. Percy helps teams automate visual testing. This Browserstack tool is used to typically capture screenshots and compare them against the baselines and display visual changes. It increases the visual coverage and helps teams to deploy code changes with confidence.

3. Declarative tools

Declarative tools have different use cases from the others but still aim to enhance test automation productivity and stability. Declarative tools that leverage ML and AI have significant abilities related to NLP, DSL, RPA, and MBTA methods. The common ground between the methods is to eliminate tedious, error-prone, repetitive actions through smart automation. While in this category we list RPA, this specific method is not solely around automation of testing, but also around automation of processes and tasks done manually.

These tools aim to enhance test automation productivity and stability. These tools leverage AI and ML and have significant abilities related to Robotic Process Automation (RPA), Natural Language Processing (NLP), Model-based Test Automation (MBTA), and Autonomous Testing Methods (AT). The main aim of these methods is to eliminate tedious, error-prone, repetitive tasks through smart automation. Some of the tools that fall under this category are:

Focusing on declarative testing, we can take as an example tools like:

Functionize
Tricentis
UIPath Test Suite
Automation Anywhere

1. Functionize:
Especially Functionize, specify leveraging NLP to create test automation scripts without any coding skills or development languages.

The major benefits of this tool type are as follows

Fast test automation creation.
No coding skills are required. Faster maintenance of test automation scenarios.

2. Tricentis:
This is an AI-driven, next-gen automation testing tool that allows Agile and DevOps teams to rapidly achieve test automation goals. It allows teams to go beyond continuous testing with AI. It allows automating end-to-end testing of software applications. This tool combines multiple aspects of software testing (test case design, test automation, test data design and generation, and analytics) to test GUIs and APIs from a business perspective.

3. UiPath Test Suite:
This is the latest Test Suite that can be used to automate and centralize the testing process and helps to launch resilient robots and ensures high-quality of every automation. The UiPath Test Suite consists of UiPath Studio Pro, UiPath Test Manager, and UiPath Orchestrator. Thus, UiPath test Suite can be used to automate tests in UiPath Studio Pro with drag and drop interfaces, helps to manage tests with UiPath Test Manager, and also helps to execute tests witn UiPath Orchestrator. Therefore, UiPath Test Suite is helping businesses with a 360 degree testing and is helping RPA developers to build more, test better, and fix never.

4. Automation Anywhere:
These types of tools should solve problems for the right persona depending on the skillset available.

4. Self-healing tools

Apply AI to testing to identify when a function has changed. Then, the test can automatically update itself to be relevant and not fail during execution. Element selection in tests is auto-corrected when the UI changes.

Code-based test automation is by nature less stable. It requires tuning constantly per platform or environment, and its entire foundation is the application objects. These objects tend to either change every few weeks, or worst case they are used inefficiently (e.g. XPATH vs. Object ID, etc.).

Some of the tools are as simple as a web browser plugin installation (Mabl, Testim). Some tools that assist in test maintenance with machine learning are richer in their abilities and are integrated into an end-to-end continuous testing solution (Perfecto, Tricentis).

Perfecto
Mabl

At the heart of these tools there is a ML algorithm that upon each execution and in between them “learns” the website and/or application under test. It scores the element locators from each screen in the app based on reliability and probability to be found successfully.

In automation tests, the problem of flakiness, reliability, and maintenance issues persist, and this is one of the main reasons why AI and ML have been introduced in test automation. To overcome these problems, self-healing tools have been developed that are mostly based on a record and playback mechanism, wherein the main ML engine resides in the self-healing of the recorded scripts. Some of the tools that fall under this category are:

Mabl:
It is the leading intelligent test automation platform built for CI/CD. Mabl crawls your app screens and begins to run default tests that are common for most applications. It also uses ML algorithms to improve test execution and defect detection.
Testim:
This tool uses AI and ML algorithms to automate testing to its full extent. AI is used to speed up the authoring, execution, and maintenance of the tests. Testim includes self-maintenance of automated tests that are ML-based. This results in the fast authoring of stable automated tests.

Best Practices for Testing AI Applications:

Assess Information Technology infrastructure

Successful execution of an AI strategy requires discipline and the best practices listed here. Responses may also contribute to adoption. Consider the use of resources in terms of the time, cost, complexity, and skill set required to build an AI model and demonstrate a business case.

Determine the use cases

Determine how the peers and competitors have strongly deployed AI platforms. Look for suppliers with a solid track record to mitigate risk. They talk to stakeholders about the utilization cases and the benefits of implementing AI.

Also, use AI accelerators from popular cloud service providers (CSPs), which may already be included in BPM (Business Process Management), RPA (Robotic Process Management), DMS (Document Management System), and iPaas (Integration Platform as a Services) platforms. Working with stakeholders and educating them on how to use AI solutions increases their likelihood of use and drives adoption across the organization.

Search for relevant use cases for the optimized deployment of artificial intelligence in each of the following areas:

Machine learning (ML)
Natural language processing (NLP)
Natural language understanding (NLU)
Optical character recognition (OCR)
Chatbots

Learn how your competitors and peers have successfully deployed AI platforms. Look for vendors with a reliable track record to reduce risk. Consult with stakeholders on your use cases and the advantages of implementing AI. Also, leverage AI accelerators from prominent cloud service providers (CSPs) that may already be included within your LCAP, DMS, BPM, RPA, and iPaaS platforms. By working with your stakeholders and teaching them how to use your AI solution, the more likely they are to use it, driving organization-wide adoption.

Understand the Raw Data

Insufficient data may lead to misrepresented results and AI implementation failure. If you can comprehend the raw data, garner your business experts’ assistance to access a detailed interpretation. Comb through the data to ensure there aren’t any typos, missing components, skewed labels, and other errors. Ensure your data samples contain every element you need to analyze. Incomplete data may cause misleading represented results and AI execution failure. Ensure that the sample data contains all the elements required for analysis.

Losing focus on the raw data can lead to skewed results and loss of confidence on the machine learning models. If you do not understand the data, get help from business experts to gain a full understanding of the story the raw data is telling you. Analyze it to ensure that there are no missing values, incorrect labels, or typos and check that the sample contains the full spectrum of all users that you wish to analyze.

Also, consider the relationship between data labels and values that you are trying to predict based on dependent data and ensure that there is no biased data (data favoring a particular result). While analyzing the raw data, you will get an understanding of the limitations of your data set and model. This will help you communicate the scope and limitations of your predictions based on the pattern of the data to your stakeholders.

Train the models

You will need high-quality historical data to train your ML models. Use AutoML engines to build image, speech, video, and natural language, recognition models. With AutoML engines, any user can upload their images and automatically create an ML model using a drag-and-drop interface. Essentially, it imports data, tags the data, and trains the model. The best part is that an AutoML engine manages all the complicated work for you.

Training an ML model requires high-quality historical data. Generate natural language recognition, image, video, and speech using the Auto Machine Learning engine (AutoML). The AutoML engine allows users to upload images and automatically generate ML models using a drag-and-drop interface. Import the data, label the data and train the model. The best part is that the AutoML engine takes care of all the hard work.

Measure and record the results

You should experiment with artificial intelligence, but you should also incorporate disciplined tracking, monitoring, and measurement at every step using a critical approach. Also, it’s essential to continually audit your deployment to ensure it consistently aligns with your business objectives. Changing your strategy is more effective than accepting failure.

Continue testing your models and predictions to drive further improvements where necessary. Keep your data clean, and retain a master raw data set to use for every testing round. You can also use your master data set to test modified use cases. Monitor your model for potential risks and issues. Don’t forget to add time for managing any unexpected problems. While performing AI tests, one should also incorporate measurement, precise tracking, and monitoring using a complex approach throughout the action.

Also, it is essential to continuously check the deployment to ensure it is frequently coordinated with the business objectives.

Guide the team and cooperate

Artificial intelligence continues to get better, but it still requires the correct data. The issue is it’s difficult to find data science experts. Therefore, invest in continuing education for your stakeholders. Add to your training initiatives by creating an environment where collaboration is part of the culture. A crucial factor for AI implementation success is change management.

Create short-term and long-term objectives of what you expect to achieve using predictive analytics and then machine learning and then natural language processing and on down the AI list. Map out how each deployment affects each business line and how it enhances your employee workflows AI continues to improve, but it still needs relevant data. The problem is that it is difficult to find data science experts. Therefore, invest in further participatory education.

Admit all the wins

Celebrate every win, and involve every executive and stakeholder. Try to complete your projects within or before 12 weeks to encourage continued engagement. As you learn from each successful project, you can scale AI across more business lines and company locations. Use your goals as success benchmarks, and focus on your results. When focusing on the outcome, keep in mind that AI platforms can take structured and unstructured data sets.

Finally, using best practices for implementing AI requires a long-term perspective. Remember that AI deployment is a marathon and not a spring. Understand what AI is currently capable of executing, and be realistic about your timelines and your expectations.

Conclusion:-

A better understanding of the differences between AI and human intelligence is needed to better prepare for the future in which AI will have the most profound effect on our lives. With the advent of AI in software testing, businesses are now able to achieve faster tests and reliable products. Leverage next-gen AI-based testing services by next-gen testing services provider to get faster and quality releases with more efficiency and accuracy.

There are best practices for implementing AI in companies like Assessing IT infrastructure, determining the use cases, understanding the data, training, and measuring the records. An AI application needs to be tested for functionality and system levels. It is similar to testing of traditional software in aspects of test planning, test modelling, test design, and execution. Testing of an AI system becomes more challenging and function test quality evaluation becomes an integral part of AI application testing.

Popular Websites to Find Software Testing Research Papers Free & Paid

Posted on March 8, 2023 by tbsupadminnxtbackendacc

Software testing is the most significant part of the Software Development Lifecycle (SDLC) as it is something upon which the final delivery of the product is dependent. It is time consuming and an intensive process, therefore, enhanced techniques and innovative methodologies are requisite.

We provide introductory information about the well as the source of the research papers for software testing, which is either free or paid.

There are very few libraries in the research area where research papers are accessible; some papers are protected by their authors; we can access the research paper by requesting or paying the appropriate amount. The impact of technology on our businesses is exciting and the opportunities for us are unlimited.

Here are some major trends for research parameters that are changing the face of software testing

1. Springer Nature:

Our very first platform that is useful for researchers is “Springer Nature”. Springer Nature is a publishing, educational, and research-based company. The company looks to provide resources primarily for researchers and scientists.

Springer Nature advances discovery by publishing trusted research, supporting the development of new ideas and championing open science. We are committed to playing our part in accelerating solutions to address the world’s urgent challenges.

There are some journals published by Springer that are specifically designed for software testers’ research. “Software Quality Journal“ and “Automated Software Engineering” are the journals where researchers can publish their research as well as some past researchers’ papers for reference. These journals are generally free to readers, but some papers are protected by the author; users can access the references after requesting access or paying access fees. For access to the Springer Nature Library, follow the link https://www.springernature.com/gp

Read Also: Personality Analysis of Software Testers A Scientific Approach

2. Clarivate

Web of Science is the world’s most powerful research engine, which is a subscription platform that gives access to many databases including reference and citation data from academic journals, conference proceedings, and other materials in a variety of academic subjects.

It was created by the Institute for Scientific Information. It is utilized for searching of a subject and cited references; for instance, it retrieves the articles that are cited by a reference article and also helps in the viewing of the references that are already cited in a relevant article.

Clarivate is the current owner which helps you collect and analyze information for insights you can easily act on. Under this, we can get the papers based on title or keywords. Based on software testing, the platform almost covers the majority of research for access to the Web of Science Library by using this link https://mjl.clarivate.com/search-results.

3. Mendeley

“Mendeley” is a reference management programme that was established in 2007 by PhD students Paul Foeckler, Victor Henning, and Jan Reichelt and was purchased by Elsevier in 2013. It is used to organise and distribute research papers, as well as to produce bibliographies for scholarly works. Following the purchase, the Mendeley team expanded its product portfolio while iterating on its core reference management application. Mendeley can track reader numbers, which have been shown to predict citation impact, although journal-level metrics are poor indicators of dependability.

It covers a large dataset about software tester research publication for more explosions Login in Mendeley and access the trending subject as references. Mendeley is a free reference manager that can help you collect references, organize your citations, and create bibliographies which manage the software that helps to manage your research data in systematic way. Below is the link which helps the researcher easily to enter in mendeley https://www.mendeley.com/?interaction_required=true

Read Also: History of Software Testing Estimation Models for Cost Analysis

4. ResearchGate

“ResearchGate” is a commercial social networking service for academics and researchers around the world that allows them to exchange papers, ask and answer questions, and locate partners i. e. it discover scientific knowledge and stay connected to the world of science While viewing articles does not necessitate registration, site members must have an email address from a recognised university or be personally certified as published researchers.

The research gate shows the result based on the title and the keywords under the banner of ResearchGate, no specific journal is designed for software testing. For reference purposes, it covers a wide range of papers in the software testing domain and getting the papers based on the title and keywords do follow the following link https://www.researchgate.net/.

5. Institute of Electrical and Electronics Engineers (IEEE)

The “Institute of Electrical and Electronics Engineers (IEEE)” is a professional society for electronic and electrical engineering, which is an organization dedicated to advancing innovation and technological excellence for the benefit of humanity, is the world’s largest technical professional society. It is designed to serve professionals involved in all aspects of the electrical, electronic, and computing fields and related areas of science and technology that underlie modern civilization. The IEEE’s aim is to advance technology for the benefit of humanity.

The IEEE has some journals that are very useful for the domain of software testing. The journals are as follows: “IEEE Access”, “IEEE Transactions on Software Engineering,” and “IEEE Software” are the three most popular journals that are useful for software tester research aspirants and there is IEEE Standard for Software Test Documentation which is a set of basic test documents that are associated with the dynamic aspects of software testing that is, the execution of procedures and code.

The role of IEEE in current technology is to advance computer and information processing science and technology; promote professional interaction; and keep members up-to-date on the latest developments. If you want to publish your article or need some standard papers for reference, go to IEEE and access them; some are free and some are subscription-based. We are providing the link for easy access https://ieeexplore.ieee.org/Xplore/home.jsp

6. Elsevier

“Elsevier” is a scientific, technical, and medical Publishing Corporation which takes a hand in shaping the future of knowledge with roles dedicated to delivering innovations and improvements to our platforms. Elsevier has Agile work flows embedded within the company which utilizes cutting-edge technological practices and focused on improving your technical skills, and they provide access to resources to help you progress.

Electronic and print editions of periodicals, text books, and reference works covering the health, life, physical, and social sciences are among the products and services offered. Academic and government research institutions, corporate research labs, booksellers, librarians, scientific researchers, authors, editors, physicians, nurses, allied health professionals, medical and nursing students and schools, medical researchers, pharmaceutical companies, hospitals, and research establishments are among the target markets. Following are the some standard Elsevier journals in the software testing domain:

1. “Security Controls Evaluation, Testing, and Assessment Handbook.”
2. “SDL ’97: Time for Testing”
3. “Practical Model-Based Testing”
4. “Usability Testing Essentials”:
For direct access to the Elsevier go through the link https://www.elsevier.com/en-in

Read Also: Software Testing Latest Trends & Technology in 2023

7. Semantic Scholar

“Semantic Scholar” is an artificial intelligence-powered scientific literature research tool created at the Allen Institute for AI and made public in November 2015. It makes use of improvements in natural language processing to produce scientific article summaries. Semantic Scholar is examined to locate primary papers of selected secondary studies and identify missing venues.

The proposed search strategy is used to check the ability to retrieve primary papers of each secondary study. The Semantic Scholar team is investigating the application of artificial intelligence in natural language processing, machine learning, human-computer interaction, software testing, and information retrieval.

Semantic Scholar summarises scientific literature in one statement. One of its goals was to overcome the difficulty of reading multiple titles and long abstracts on mobile devices. It also aims to guarantee that the three million scientific articles published each year reach readers. Basically, it is the collection of databases of all the types of research libraries available here; basically, it is domain-independent. We can search the article on this platform by applying some filters such as subject, domain, title, keywords, etc. We provide a link to Semantic Scholar for research aspirants to easily search any research article in any domain. https://www.semanticscholar.org/

8. ScienceDirect

“Science Direct” is a website that gives access to Elsevier’s enormous bibliographic collection of scientific and medical publications. It emphasizes developing a strategy for testing and validation and show how to design a testing and validation program that deliver information in a timely and cost effective manner.

Researchers, teachers, students, healthcare and information professionals use ScienceDirect to improve the way they search, discover, read, understand and share scholarly research.

ScienceDirect combines authoritative, full-text scientific, technical and health publications with smart, intuitive functionality so that users can stay informed in their fields and can work more effectively and efficiently. Article abstracts are freely available, but full text access usually needs a membership or pay-per-view payment, unless the material is freely available via open access.

The following journals are relevant to the software testing domain:

1. Advances in Computers
2. Perspectives on Data Science for Software Engineering
3. Journal of Systems and Software
4. Applied Soft Computing
5. Information and Software Technology
6. Information Sciences.

These journals are very useful for researchers in terms of publication and reference purposes; however, some articles in these journals are author-restricted and require access permission. We’ve included a link to ScienceDirect home page for your convenience https://www.sciencedirect.com/.

Get ready to quick access to check the remarkable software testing platforms

Platforms for research parameters	Link
Springer Nature	https://www.springernature.com/gp
Web of Science	https://mjl.clarivate.com/search-results
Mendeley	https://www.mendeley.com/?interaction_required=true
Research Gate	https://www.researchgate.net/
IEEE	https://ieeexplore.ieee.org/Xplore/home.jsp
Elsevier	https://www.elsevier.com/en-in
Semantic Scholar	https://www.semanticscholar.org/
ScienceDirect	https://www.sciencedirect.com/

The software development industry has devolved into a front line. Every company wants its product to be the greatest and in order to make your product the greatest on the market; you must ensure that it is of the highest quality.

Conclusion

The primary goal of this blog is to provide a research sources used for references and to help aspiring researchers in their search for researchers.

Improving Software Test Automation Using Different Algorithms

Posted on February 7, 2023 by tbsupadminnxtbackendacc

In order to deliver a flawless product to customers, software testing is a technique performed by software development organisations to assess the quality of the programme. To design the product, the needs of the customers and their recommendations are explored. The items must be supplied to the clients after adequate validation and verification, which lessens the burden on the firms after the products are released.

Introduction to Current Trends

The current trend in software testing that better meets industry demands is the growth of dependability models. Since verification and validation are carried out by distinct people in a typical testing procedure, efficient automation offers a stronger link between the two than does that approach. These automated processes are necessary for real-time applications since they form the core of unified testing, which also includes manual testing.

The technique of manual testing is used to examine the system design and find problems based on test cases. It takes a testing developer with the necessary understanding to complete this repetitious procedure. An automated testing environment is created with multiple levels of abstraction under various domains and a wide variety of diversity rules in order to eliminate the problems with manual testing. Industry-wide automated testing’s overarching goal is to speed up computations and cut costs.

Concept required to grow the Business

Many businesses still use outdated test automation techniques that have negative effects, such as the inability to automate useful tests, produce and maintain automated tests at the lowest possible cost, or promptly identify errors. Such unfavourable consequences prevent businesses from gaining the benefits of test automation they anticipate, use up resources for software development, and potentially jeopardise software quality. “Increasing immature test automation processes with poor effects” is referred to as “improving test automation maturity” in the software industry and research community.

Although there have been more initiatives in the software industry to promote test automation maturity, not all of these efforts have been successful. According to a recent poll on software testing practises, around 65% of the almost 2000 software businesses worldwide sought to increase test automation maturity, but only about half said their efforts were successful. To develop test automation maturity effectively, the industry requires the guidelines.

Software testing, which is based on standard verification over static and dynamic environments, aids in improving product design. In a static environment, verification is carried out using formal processes and methods, but in a dynamic environment, verification is carried out at any level using test cases. Dynamic analysis is more effective than static analysis and can spot mistakes in product design.

Early-stage testing decreases product problems by discovering defects and reducing product failure after implementation. Software testing makes use of straightforward tests and code procedures to cut down on mistakes at every level of the programme. When it comes to the verification and validation processes, the selection of the best product is examined in the former, whilst the product’s qualities are examined in the latter. It enables the client or user to examine the programme that has been created and make necessary corrections to meet their demands.

Data on the item or service being evaluated is gathered during the software testing process. Running programmes or apps while testing allows you to find and repair bugs. The process of developing test cases is crucial for getting the most out of the system and spotting as many errors as possible early. Throughout the whole software development process, this is the most economical use of time and resources. Automated testing is unable to carry out comprehensive testing.

Recent work on a novel application using the Intelligent Security and Automation System (ISAS) architecture has revealed that robotic testing dramatically cuts the price and time required for trials, which is crucial for monitoring a project’s development. It is critical to adhere to the evaluation approach in order to construct the best test suites.

Aspects and Objective

The most important stage of any product development is testing. The testing stage serves as the last checkpoint for any rejections or commission errors. Testing computer programmes is a little more challenging than practising a framework to make sure it functions as intended. When in doubt, it is critical to keep in mind that each inquiry, audit, survey, or walkabout is a test. If there have been more successful static testing attempts, there will be less problems with dynamic testing. IT has frequently demonstrated that the incremental cost of resolving an issue decreases with the speed with which it is identified and fixed. The process of testing starts with the representation of an item. All evolutionary algorithms yield results that are close to those of the Genetic Algorithm. When exposed to a certain set of environmental circumstances, tests are done to make sure that a product or service satisfies specified requirements.

There are two aspects to this objective. The main objective of this fragment is to confirm the accuracy of the requirements point of interest for the item. The settings and code are excellent fits for every criterion, as shown in the second part. For a job to be deemed exact, all affirmation requirements must be satisfied.

Problems in software test automation

The following actions are mainly responsible for problems in software test automation:

Unfounded hopes for automated testing

It goes without saying that test automation has several advantages. Most significantly, it saves time, energy, and resources for the QA team. Does this not imply that increasing the number of procedures that are automated would increase efficiency? Not exactly. People’s unrealistic test automation expectations can ruin the entire testing process.

Manual testing is important. Manual testing should never be disregarded. In certain cases, manual testing of an application is far superior to developing automated test scripts.

Manual testing is appropriate for:

Usability testing for UI
Quick compatibility testing using, say, one or two devices
One-off tests
Ad-hoc analysis
Testing for both localization (L10N) and internationalisation (I18N).

There are still manual testing components. Those who support automated test scripts are necessary. Therefore, even if you insist on automating as much of your testing as possible, there will still be manual tasks to complete.

Solution: A well-defined testing plan.

Using inappropriate tools

If the proper tools are not used, test automation will not be efficient. With so many testing options available, it is simple to become misled. The poor tool selection might lead to scalability issues in addition to the failure to achieve your initial test automation goals.

Solution: Make judicious tool selections.

Automate pointless tests while ignoring crucial test cases

Unfortunately, QA teams frequently begin the automation process by arbitrarily automating test cases. They now have an excessive number of pointless tests and little test coverage. Additionally, by using this method, you run the danger of not include all pertinent cases and having poor software quality.

Solution: Determine what is worth automating.

Incorrect testing window

Many teams still consider testing to be something that happens after development. QAs begin their work only when the entire build has been completed. This antiquated method cannot ensure excellent software quality. It does not allow QAs to adequately test all levels, and there is typically not much time left for testing.

Solution: Run automated tests concurrently with development.

Inadequate testing

This is the most difficult of the test automation difficulties. A lack of appropriate testing arises when QAs depend too heavily on automation and focus on passing tests rather than detecting issues. The problem is that automation creates a false sense of security. It is tempting to limit human interaction and accountability for the outcomes when automated tests run regularly. Such an approach has disastrous consequences, such as poor test design and inconsistent and inefficient testing.

Solution: Training for the QA staff.

Improving test automation using genetic algorithm

Software should be tested once it has been created. A study by NIST indicates that software flaws have a significant negative impact. As a result, the test stage of software development is one of the most delicate stages and accounts for around 50% of the total cost. The cost of software testing has been greatly reduced by the introduction of automated software testing tools since it uses a lot of resources but does not offer any new functionality to the product. Various techniques for automatic software testing have been developed over the past ten years with the goal of maximising error detection while generating the fewest amount of test input data possible.

One of the algorithms that has been extensively employed in the area of test data creation automation is the genetic algorithm. Traditional genetic algorithms are effective at producing useful test sets, but they take a long time. Applying prior knowledge to the issue or including a local search phase in the evolutionary cycle can help to some extent. Chromosomes do not attempt to enhance themselves; instead, they only wait for a mutation or recombination to haphazardly improve them. This is a notable flaw in the genetic algorithm. Additionally, the genetic algorithm treats each segment of a chromosome as a whole and does not distinguish between its many sub-sections. Due of this, a genetic search is extremely comparable to a blind search.

The advantages of genetic algorithms are as follows:

They exhibit an unpredictable pattern that can be statistically assessed but cannot be precisely predicted (i.e., stochastic).
Another area where it thrives is big data. It works well with probabilistic and non-deterministic rules.
It’s an excellent tool for simultaneously optimising several objectives. This method has certain shortcomings.
It can take a lot of time, use a lot of computer resources, and be difficult to create objective functions.

Improving test automation using AI

Automation of the testing procedure and quality control results in considerable time and resource savings. However, there are a few things to think about when using AI and machine learning for test automation. We go through the six factors to take into account when using artificial intelligence and machine learning for test automation.

1. Visual evaluation testing (UI)

Software engineers do visual testing as part of their quality control procedures. They assess if the application functions and appears as intended for the user. Understanding the sorts of patterns that machine learning can detect is crucial. Manual inspectors are better able to spot imperfections, whether they are noticeable, aesthetic, or functional.

While analysing complicated surface textures and picture quality, a typical machine vision system may need a thorough review. Therefore, visual assessment of online or mobile apps is better suited for a deep learning tool or system.

It delivers quick and precise outcomes. Developers can rely on this technology in situations when human intervention might be deemed dangerous. Developers may eliminate manual testing and immediately find visual issues by implementing a quick machine learning test.

2. API Testing

Software testing of the Application Programming Interface (API) allows data flow and communication between two software systems. The benefit of API testing is that it is more accurate than UI testing at identifying application flaws. When the test fails, it is simpler to examine the source code. It can withstand application modification, which facilitates automation.

To get thorough test coverage while testing at the API level, you require a greater level of technical know-how and equipment. Additionally, software testers need to be knowledgeable in their respective fields. It is crucial to take into account if testers have a thorough understanding of various application interfaces.

AI allows you to transform manual UI testing into automated API tests that handle all the labor-intensive tasks. You will be able to connect the actions taken in UI tests to API tests as a novice.

3. Domain expertise

In software testing, domain knowledge is essential. With artificial intelligence, you can test apps more effectively whether they are subjected to human or automated testing. For instance, developing test scripts in Java, Python, or C# might be difficult. Advanced testing technologies allow the creation of test scripts and codes by testers. AI enables robots to self-write faultless code.

Manual testing is preferable to handle complicated test scenarios, though. You would be able to determine when to execute test cases using manual or automated testing if you had sufficient domain expertise. Knowing how the application will function and help the company is crucial when implementing AI in test automation. We should typically anticipate failure in results while executing test automation. No matter how little, important, or serious the application fault is, it must be easy for QA teams to scale it.

4. AI Spidering

Writing test scripts for test automation is most frequently done via spidering. It contains a feature that allows you to use AI/ML technologies to direct users to your web application. The application then automatically starts to crawl over itself while scanning and gathering data.

As you perform tests, the tools gradually assemble a dataset and develop patterns for your application. When you use this tool again, it will identify possible problems by referring to its collection of patterns and behaviour.

Though some of the distinctions might not be relevant, keep that in mind. In this instance, a subject matter expert will need to confirm whether the problem that ML has identified is a bug or not.

Understanding which components of an application should be evaluated will be made easier by spidering AI. Simply said, machine learning will handle difficult jobs, and a tester will need to confirm the accuracy of the output.

5. Test Scripts

When a code has been changed, it will be challenging for software testers to estimate how many tests are necessary. Artificial intelligence-based automated testing solutions can determine if a given application needs numerous tests or not.

The use of AI in testing has two advantages. You can save extra time by ceasing to run tests that are not necessary. It is practical to evaluate a system’s overall performance without running the test scripts again. As a result, you don’t need to manually check on it every time.

6. Automated Tests by Robots (RPA)

RPA is the name given to software that automates repetitive commercial tasks without involving any human beings. It assists in fully maintaining and automating the interfaces already present in IT systems. RPA scans the screen, uses the systems to traverse, then locates and collects data.

The tests may be run via online, desktop, or mobile apps, and the duties are entirely handled by the bots. It assists with test data setup and regression test execution.

RPA testing initiatives are undoubtedly being taken by many businesses. However, business testing is powered by RPA, which may reduce the amount of testing that testers complete. Scalability, codeless testing, cost savings, higher productivity, precise findings, and adaptability are among RPA’s key benefits.

Artificial intelligence can automate about half of the test procedures. Machine learning may be used by testers to train systems to find mistakes that manual testing might miss. You may speed up the process of getting reliable findings by incorporating AI into your test automation. Since AI handles the majority of the testing procedure, you can save time.

Automation has a significant impact on the software industry’s ability to increase test efficiency. Projects use extra people for manual testing or utilise automation tools or techniques to increase the amount of test automation in order to ensure test coverage satisfaction and hence lower risk. The option relies on whether the project cycle time or test time is reduced. The significance and necessity of automating software testing have grown as a result of rising software usage, increasingly complicated software functionalities, and shorter timeframes for evaluating programme quality. By applying machine learning to automate software testing, mistakes in manual testing are reduced and assessment is sped up.

Because it helps software testing companies to boost their test efficiency, automation is essential in the software business. In order to assess created software with a range of drawbacks, a number of automated approaches have been conceived to provide test data, approaches based on genetic algorithms being one of them.

How Many Roles Can a Software Tester Play

Posted on February 1, 2023 by tbsupadminnxtbackendacc

Software testing involves inspecting a programme or application to ensure that it performs as intended. It is an essential part of the software development life cycle since it prevents spending a lot of money and time on addressing software bugs. A business may avoid several significant mistakes in the software development life cycle by having a solid grasp of when and how to execute software tests. Although each organisation has its unique team structure, there are several roles that are essential to the testing process’ success.

A software tester will take part in quality assurance as well as deployment of the software. You will also be in charge of running both automated and human tests to ensure that the code written by developers meet the requirements of the task and that any bugs or errors are fixed before the final product hits the market.

The role of a software tester is of great importance to the development of technology-based products, including software systems and cars, electronics, defence as well as healthcare. You could work on specialised, one-of-a-kind projects or globally distributed, multibillion-dollar enterprises.

Software tester as Scrum Master

After doing some in-depth research, I’ve come to the conclusion that some of the qualities needed to be a Scrum Master are already present in the position of a software tester.

There are more similarities between the two jobs than differences, like:

1. They are in charge of overseeing the procedure and are committed to enhancing quality by assisting the development team in producing high-quality items.

2. They assist in establishing the user acceptability criteria and are knowledgeable about corporate needs.

3. They are confident that every need for admission has been satisfied.

4. Regarding the notion of done, the tester and the Scrum Master ensure that all the user stories are finished at the conclusion of each sprint.

5. They support the software development lifecycle’s overall goal of continual improvement.

6. They promote the development team’s productivity and cooperation.

7. They must plan ahead proactively to reduce pressure during the testing phase and later stages of the software development lifecycle.

8. They can find issues and flaws with the system.

9. They are able to evaluate the danger of any change.

10. They possess social and soft skills

Aside from the traits that these two jobs have in common, each of these roles requires a different set of skills, which help each project progress smoothly.
As a Scrum Master, the tester develops the ability to observe team activities on a daily basis and get insight into the project’s progress as well as expertise of the product. They also learn how to listen carefully and pay attention to the difficulties the development team faces every day. They proactively stop issues and flaws as a result.
Having the tester and Scrum Master positions under the same person is advantageous for a team as well as for an organisation operating in Scrum or wishing to change its development process to Scrum. Participating in the development process and gaining knowledge from various stages of the process aid in locating the key difficulties. Due to this, someone who performs the dual roles of tester and scrum master will offer a unique viewpoint, enhancing the entire development process and assisting the team in producing deliverables of higher quality. Additionally, they will benefit the process and be better equipped to influence the development team.
A tester may also make the ideal Scrum Master, given the correct conditions!

Software tester as Release Manager

Within the field of software development, the procedures of quality control and release management are intertwined. They are two branches that work closely together and frequently merge to form one team or individual. You could say that QA and RM are inseparable, that they must always be in touch, and that they cannot afford to take a break. In this article, I’ll go over the fundamental rules that every quality tester should adhere to and comprehend regarding the procedure of software release management, bringing both areas together in the pursuit of creating high-quality software.
A tester’s primary responsibility is to run tests to ensure software quality and verify that earlier work is free of mistakes. The success of the implementation greatly influences how well the testing process goes. The QA team will be able to spot numerous flaws that may be connected to the implementation phase if the tester thoroughly followed the development process and is aware that the back-end and front-end teams ran into specific issues when implementing the code. Consequently, it will also be simpler to suggest the appropriate solution to the appropriate teams.
Testers will comprehend and value the significance of completing their jobs within the scheduled timeframe if they are aware of how the implementation process has evolved. If testers were properly informed about the software deployment process, many problems may be prevented.
If the tester and the release manager are the same person, the organization’s working efficiency suffers slightly because they have similar thinking styles and problem-solving perspectives.
The dependency also decreases, and proficiency increases, which is good for the organization.

Software tester as Project Manager

The project manager is accountable for the final product’s quality and on-time development. In order to balance the costs of the job, workflow productivity, product dependability, capabilities, and development time, he must use new resources or, if necessary, reallocate those that are already accessible. The issue tracking system’s database becomes a crucial source of knowledge about the present status of the product and its adherence to the requirement specification during this activity.
An expert in quality assurance (QA) is aware of exactly how software products need to behave instead of how a product manager imagined they ought to. A creative software quality tester shouldn’t have any trouble trying to succeed as a software product manager.
Who, in essence, is a software tester? A software tester is a remarkable person who serves as the final stage of the web development lifecycle. He stands as the final person between the client and the web developer.

Similar traits of a project manager and a software tester

1. Honesty

One of the most important talents that software project managers must consistently keep in mind is that it takes their actions, not just their words, to establish a certain business as usual for a group. This skill is comparable to the abilities necessary for software testers. reasonable managerial demands and demonstration of moral behaviour.
The honesty that underpins project management or leadership refers to a set of principles, a commitment to sincerity, and consistency in teamwork. Sincere software project managers accept responsibility for creating high standards for moral behaviour for themselves and for rewarding those who uphold these standards.

2. They make wise decisions.

A software tester’s ability to make sound decisions is one of the key duties and obligations of project managers on software projects.
The excellent project manager position in software project management is crucial for both personal and professional success. The best project management software is used to decide on a number of options that will assist define the project’s course.
We all know that even a small mistake in a choice may quickly put the entire enterprise in jeopardy. A software tester should be capable of thinking quickly and responding decisively in this way.

3. They Encourage a Common Vision

In software development, the productive tasks of the project manager are typically characterised as having a vision of the future and the ability to articulate it. A software project manager is a person who empowers you, gives you a sense of purpose, and provides you with the vision and spirit to transform.
People are empowered by the creative project managers to feel like they truly matter to the work.
The software tester also gives their co-workers the opportunity to experience their own vision and gives others the option to create their own vision, explore what the vision will mean for their jobs and personal life, or even see their future as a key component of the association’s vision.

4. They are excellent at solving issues!

The finest project management position in software development is to collaborate with a team of professionals and use their expertise to solve problems in the most effective manner.
Only the roles and responsibilities of software testers will foresee that the software project managers will have a prepared response in due time regarding every issue; software project managers are required to be able to use the knowledge of their partners and even colleagues to create an aggregate reaction to any issues they encounter on their approach to delivering a project.
The only person who truly understands how and when it will be best for the end user to interact with the programme is a software tester. This isn’t, exactly, the question of online usability. The only person who can judge if something is done effectively or not is the tester, who uses the software product themselves several times while testing it. A tester then specifies how it must be.

Conclusion:-

This article shows how software testers are versatile and able to play various roles along with performing testing tasks. In this article, we will attempt to cover the actual role that the tester can play and how to be helpful in making things easier. After conducting research and consulting with various sources, we concluded that the qualities required of a scrum master are already present in a QA tester.

The software tester is successfully able to do the responsibilities of the release manager; if one person plays both roles, it will help them complete their jobs within the scheduled timeframe. If a software tester takes on the project manager role, the organisation benefits because they share qualities such as honesty, decision-making ability, vision, and problem-solving skills. As per research and literature, it is proved that testers play various roles and are helpful for achieving milestones in the software profession.

An Analysis of the Effects of the Agile Model in Software Testing

Posted on January 30, 2023 by tbsupadminnxtbackendacc

Software professionals are under pressure to discover and measure quality aspects including usability, testability, maintainability, and dependability as well as engineering methods that assist the creation of high-quality products with these advantageous characteristics. Like other engineering objects, the software development process has to be designed. In other words, it has to be developed, put into practise, assessed, and maintained. The finest technical and management techniques must be incorporated in a methodical manner throughout the software development process, just as in other engineering disciplines.

Agile development approaches are becoming more popular among companies that are under pressure to provide apps of a better calibre in order to remain competitive. Agile and other iterative techniques are actually taking over as the industry norm for creating applications. Agile’s ideal goal is to accelerate the delivery of the greatest amount of business value possible by putting an emphasis on people and ongoing development. Although the agile technique is typically thought of as primarily relevant to development teams, the entire organisation must adapt.

Agile development confronts businesses with two significant challenges: being flexible enough to keep up with the iterative nature of the agile approach, and providing quality and stability to applications much earlier in the development process in order to align with the business.

The fundamentals of agile testing

The fundamental tenets of agile testing are as follows:

1. Working software is the main gauge of success in this Agile testing strategy.
2. Self-organizing teams have the highest chance of success.
3. Our first aim is to consistently and promptly deliver high-quality software.
4. Daily activity gathering is required of software engineers throughout the project.
5. Increasing agility through steady technology advancement and superior design.
6. Agile testing, which offers continuous input, makes ensuring that the final product lives up to the business’s expectations.
7. The Agile Test approach requires us to carry out the testing process as we implement it, which cuts down on the amount of time needed for development.
8. The Agile testing methodology should focus on maintaining a constant development speed.
9. Regularly reflect on ways to improve your effectiveness.
10. Self-organizing teams provide the finest architectures, requirements, and designs.
11. The team evaluates and modifies its behaviour to improve efficiency at each meeting.
12. The most effective and efficient way to share knowledge within the development team is through face-to-face conversations.

Process of Testing Software

Software testing is a technique for confirming and validating the software; it ensures that the software/applications are executed without errors or problems. An agile model created to satisfy all technical and commercial requirements. When applied, this model may be constructed with the same qualities and will function as intended. Software testing finds program/software bugs, mistakes, and faults. The software testing procedure must include fixing these faults, mistakes, and defects. When programme updates are made, the software should be tested once again and then once more after that, until all flaws have been discovered and corrected. The testing process and the condition of the software under test are monitored and reported on during test operations.

Important flaws are checked during test planning by going over the requirements and design papers. The testing team fixes these flaws but is unable to raise the software’s quality. Prior to testing, all enhancements should be implemented into the system, therefore they should all be recorded during the coding phase of software development. If software architects and designers acquire all the improvements within a certain time limit, they will have created a good model. The design of the software or application can be improved by testing before coding.

Pros and Cons of the Agile Model

Agile methodologies are now extensively used in the software industry, however they might not necessarily be appropriate for all products. The agile paradigm has the following benefits and drawbacks.

The following shows the benefits and drawbacks of the agile model:

Pros

Is an extremely practical method for developing software.
Encourages collaboration and cross-training.
Functionality can be quickly built and proven.
Minimum resource requirements.
Adaptable to both changing and fixed needs
Provides early, imperfect answers.
Effective model for continuously changing surroundings.
Few rules, simple to use documentation.
Allows development and delivery to occur concurrently within a larger, planned environment.
Requires little to no planning
Simple to handle
Provides developers with flexibility

Cons
Ineffective for managing complicated dependencies.
A greater risk of extensibility, maintenance, and sustainability
Without an overarching strategy, an agile leader, and an agile PM practise, it will not succeed.
The scope, functionality to be supplied, and modifications to fulfil deadlines are determined by strict delivery management.
Relies significantly on client contact; as a result, if the consumer is unclear, the team may be led astray.
Since little documentation is produced, there is a great deal of individual dependence.
The absence of documentation may make it difficult for new team members to learn technology.

Commercial Agile Testing Methodology

Agile testing is currently widely utilised in industries since it entails close customer participation and short week cycles. Due to all these qualities, the project moves very quickly. The shortcomings of the V-Model and the Waterfall Model are eliminated, making it the optimum technique.

For projects with shifting needs and unclear project scope, it is the optimum model. Customers are more confident and satisfied with the finished product as a result of the regular customer participation at every stage, which also reduces the likelihood of future defects. Since there is client engagement throughout every cycle, the final product that is given at the conclusion of each cycle meets the criteria.

Agile testing also lowers project costs since workable products are supplied in increments after each cycle, reducing the likelihood of future defects. Additionally, this process improves communication and team trust in QA.

Due to its benefits, lower delivery costs, and other qualities in the modern industry, Agile is now a new and one of the methodologies that takes the longest to adopt.

Distinguish between Agile Testing and Waterfall Testing

The Development Life Cycle activities take place in phases that are sequential in a Waterfall Development approach. As a result, testing is a distinct phase that begins only after the development phase is over.

The key distinctions between Agile Testing and Waterfall Testing are as follows:

Sr. No.	Agile Testing	Waterfall Testing
1.	Testing takes place concurrently with development and is not a distinct step.	Testing is a different stage. Only when development is complete can testing at all levels and levels begin.
2.	Developers and testers collaborate.	Testing is a different stage. Only when development is complete can testing at all levels and levels begin.
3.	The creation of requirements involves testers. This aids in establishing the acceptance criteria and linking requirements to behaviours in the real-world scenario. Along with the criteria, logical Acceptance Test Cases would also be prepared.	It’s possible that testers are not involved in the requirements phase.
4.	Acceptance after each iteration, testing is carried out, and client feedback is gathered.	Acceptance Only the last stages of the project is tested.
5.	Regression testing may be used whenever new functions or logic are published because each loop finishes its own testing.	Regression Testing can only be put into practise once development is finished.
6.	There are no wait times between coding and testing.	Regular gaps of time between coding and testing
7.	Testing that is on-going and involves many test levels.	Test levels cannot overlap since testing is a timed activity.

Conclusions

The agile method has been in use for a while. It has proven essential in many of the intricate projects that both small and large businesses are now working on. The most creative businesses of today and future will keep pushing the boundaries of agile methods. For them, the ability to develop, plan, and carry out initiatives successfully in a fast-paced, dynamic environment will be the difference between just existing and thriving. Making the proper judgments throughout project execution as well as planning is a key component of agility.

Testing methods, skills, techniques, and equipment may need to shift in order to handle that sort of change. The mechanics of test execution are one area of software testing that does not change merely because the project team is utilising an agile strategy to build software, although certain testers may need to significantly alter their testing methodology if they are to be useful on an agile software project. Agile testers must decide what work to complete next, how to complete it, how to make it relevant to the client, and how to exercise the application in various ways to enhance their understanding of how things operate and potential risk areas.

A Study Towards Regression Testing Techniques and Tools

Posted on January 13, 2023 by tbsupadminnxtbackendacc

Regression testing verifies that no new mistakes have been added to the programme after the adjustments have been made by testing the modified portions of the code and the portions that may be impacted due to the alterations. Regression is the term for anything coming back, and in the context of software, it refers to a defect.

When should you do regression tests?

1. When a new feature is added to the system and the code is changed to accommodate and incorporate that feature with the current code.
2. When a software flaw has been found and is being fixed by debugging the code.
3. When a code change is made to improve performance.

Regression testing procedure:

Initially, anytime we make changes to the source code for whatever reason—such as adding new functionality or optimising existing code—our software fails in the previously created test suite for apparent reasons when it is run. After the failure, the source code is debugged to find the program’s faults. The necessary changes are done after finding the problems in the source code. Then suitable test cases are chosen from the test suite that already exists and covers all the updated and impacted portions of the source code. If more test cases are needed, we can add them. Regression testing is ultimately carried out utilising the chosen test cases.

All test cases are chosen with in this manner from the test suite that is already in place. Although it is the simplest and safest method, it is not very effective.
Randomly choose test cases: This strategy involves choosing test cases at random from the test suite already in place; however, it is only effective when every test case has an equal capacity to identify faults, which is extremely uncommon. Because of this, it is rarely used.
Choose test cases that cover and test the updated portions of the source code and the parts that are affected by these modifications are chosen in this approach.
Pick higher priority test cases: In this method, each test case in the test suite is given a priority code based on its capacity to identify bugs, client requirements, etc. The test cases with the greatest priorities are chosen for regression testing after giving the priority codes.The test case with the highest priority is ranked first. A test case with priority code 2 is less significant than one with priority code 1, for instance.

Tools for regression testing: In regression testing, we often choose test cases from the current test suite itself, ; so, we don’t need to compute their expected outcome and it can thus be readily automated. Automating the regression testing process will be extremely effective and time saving.

The following are the most often used regression testing tools:

Selenium
WATIR (Web Application Testing In Ruby)
QTP (Quick Test Professional)
RFT (Rational Functional Tester)
Winrunner

Regression testing provides the following benefits:

It makes sure that no new defects have been created after the system has received new functionality.
Since the majority of the test cases chosen for regression testing are already part of the test suite, their anticipated results are known. As a result, automated tools may readily automate it.
It aids in preserving the source code’s quality.

The drawbacks of regression testing include:

If automated tools are not employed, it may take a lot of time and resources.
Even after relatively minor modifications to the code, it is necessary.

Selenium

It is one of the best automated tools for testing web applications for regression. You may use Selenium Web Driver to create robust browser-based regression automation suites and tests.

A selection of Selenium’s functionalities is available for automating web applications. It is still one of the best tools available for cross platform and browser-based regression testing. Data-driven testing and automated test scripts that cycle over data sets are supported by Selenium. For large-scale quality assurance teams with knowledgeable testers, this is the right course of action. However, small and mid-size teams struggle with its high learning curve.

Features of the Tool:

Selenium supports several OSs, browsers, and environments.
It works with many different programming languages and testing frameworks.
It is, without a doubt, a fantastic tool for performing regular regression testing.

WATIR (Web Application Testing In Ruby)

A Ruby programming language-based open-source package, Watir stands for Web Application Testing in Ruby. It allows for the creation ofto create and maintain simple-to-read and maintain tests on a light and adaptable user interface.

Watir enables a range of user interaction features for website testing, including the ability to click links, complete forms and validate texts across a number of browsers.

Features of the Tool:

Extremely portable and user-friendly gadget
Excellent browser interaction features are included with this programme.
Designed to test web applications.
Enables the creation of understandable, maintainable, and easy automated tests.
Support for cross-platform technologies
Numerous large corporations, like SAP, Oracle, Facebook, etc., use it
Technology independent

QTP (Quick Test Professional)

It is an automated functional testing tool that consumes high resources and requires a license. QTP provides customer support in the form of selenium community forums. For parameterization in QTP, built-in tools are available. QTP supports only Windows and VB Script. There is support for testing on both web and desktop-based applications. There is built-in test report generation within the tool QTP, and there is a built-in object repository in QTP. QTP is user-friendly, and there is a build-in recovery scenario in QTP. Browsers supported in QTP are specific versions of Google Chrome, Mozilla Firefox, and Internet Explorer.

Benefits of Automation using QTP

It allows for recording and replay.
It allows testers refer to the screen object attributes when recording scripts on an active screen.
It has a great system or procedure for identifying objects.
It supports a variety of add-ins, including those from PeopleSoft, Oracle, Java, SAP, NET, and others.
Through an active screen, you may improve the current tests even without the AUT.
It supports well-known automation frameworks, including data-driven testing, modular testing, and keyword testing.
It has an internal IDE.
It can be connected with test management programmes like Winrunner, Quality Center, and Test Director.
It is simple to manage several suite kinds, including Smoke, Regression, and Sanity.
It works with XML.
Through QTP, test reporting is possible for analytical purposes.
Easily maintained.

RFT (Rational Functional Tester)

An object-oriented automated functional testing tool called Rational Functional Tester can run automated functional, regression, GUI, and data-driven tests. HTML, Java,.NET, Windows, Eclipse, SAP, Siebel, Flex, Silverlight, Visual Basic, Dojo, GET, and PowerBuilder programmes are just a few of the many applications and protocols that RFT supports.

Benefits

The following are the primary advantages of Rational Functional Tester:

Reusability: Tests may be immediately performed on several iterations of an application, cutting down on the time required for regression testing.
Consistency: The exact same actions will be taken each time an RFT script-based test is executed.
Productivity: Automated testing is quick and flexible, requiring no additional resources.
Rational Team Concert and Rational Clear Case are two source control management technologies that RFT interfaces with. Users may manage their RFT functional test assets using either Rational Clear Case or Rational Team Concert by integrating RFT with these source control management programs.
RFT and Rational Quality Manager have excellent integration. Users may run test scripts from within Rational Quality Manager after integrating RFT with RQM using the adaptor.

Features

Broad skills match: The RFT tool is designed for users with a range of technical skills to ensure that your quality assurance team is not limited to basic testing and that other subject matter experts in your company can participate in and comprehend the test flow using a visual storyboard format.
New software versions can employ user interface features that technology has learned, reducing time spent writing new test scripts.
Automated scripts – Rational Functional Tester gives your development teams the ability to write scripts with keyword associations that are simple to reuse, increasing productivity.
Using the Eclipse Java Developer Toolkit editor, your team may quickly and easily develop Java test scripts. It includes sophisticated debugging features and automates code completion

Read Also: How Much Does App Testing Cost?

Winrunner

For functional testing, Win Runner is a popular automated software testing tool. Mercury Interactive created it. C and web technologies including VB, VC++, D2K, Java, HTML, Power Builder, Delphe, and Cibell (ERP) are supported. WinRunner makes it simple to create tests by capturing your application development process. You may navigate your application’s GUI (Graphical User Interface) elements by pointing and clicking.

A test script written in the C-like Test Script Language is generated by WinRunner. With hand programming, we can improve our test scripts even further. The Function Generator, which is part of WinRunner, makes it simple and quick to add functions to our recorded tests.

The crucial features of WinRunner include:

We are able to do functional and regression testing on a range of application software created in languages, including PowerBuilder, Visual Basic, C/C++, and Java. Additionally, we are able to test ERP/CRM software programs.
Runs tests on many browser settings, including Internet Explorer and Netscape Navigator, as well as all versions of the Windows operating system.
In the “record” mode, we may record GUI operations. A test script is automatically generated by WinRunner.
To compare actual and anticipated outcomes, we can add checkpoints. Bitmap checkpoints, GUI checkpoints, and web links are some examples of the checkpoints.
It offers a tool for test case synchronization.
A recorded test may be transformed into a data-driven test using Data Driver Wizard. So, within a test script, we may swap out data for variables.
During automated testing, database checkpoints are utilised to validate data in a database. We will maintain database integrity and transaction correctness by highlighting the records that are added, removed, changed, or updated.
WinRunner is taught to detect, record, and replay custom objects using the Virtual Object Wizard.
The reporting tools offer the ability to create test results automatically and examine flaws.
Many testing-related tasks may be automated by integrating WinRunner with the testing management programme, TestDirector.

Silktest

Silk Test is a solution for corporate application regression and function testing. It was first created by Segue Software, which Borland purchased in 2006. Micro Focus International purchased Borland in 2009. QA Partner was the original name of the product from 1993 to 1996.

Silk Test provides a range of clients:

Silk Test Workbench supports visual automated testing (much like the previous TestPartner) and uses the VB.Net scripting language.
For automated scripting, Silk Test Classic makes use of the domain-specific 4Test language. Similar to C++, it is an object-oriented language. Classes, objects, and inheritance are all used.
UFT Developer, formerly known as Silk4J, enables automation in Eclipse using Java as the scripting language.
UFT Developer, formerly Silk4Net, enables the same functionality in Visual Studio using VB or C#.

Conclusion

An essential component of software development processes is test automation. Similar to this, automated regression testing is regarded as a crucial component.

Product teams may obtain more detailed feedback and react immediately with a speedy regression testing procedure. Regression testing finds new vulnerabilities early in the deployment cycle, saving firms the expense and work of fixing the accumulated flaws. Apparently, a little change can occasionally have a cascading effect on the product’s essential capabilities.

Because of this, developers and testers must not let any modification—no matter how small—that falls outside of their sphere of influence.
Functional tests don’t take into account how new features and capabilities interact with the old ones; they merely look at how they behave. Therefore, determining the main cause and the product’s architecture is more challenging and time-consuming without regression testing.

Evolution of Software Testing & Empirical Study on Software Test Effort Estimation

Posted on December 20, 2022 by tbsupadminnxtbackendacc

As software programming has developed over the years, testing, a crucial component of software development, has also undergone a number of modifications. The beginning of it all was the programming and debugging phases, when identifying problems during debugging was seen as testing. Testing was given a distinct identity and handled as a distinct activity from the debugging process in 1957.

Testing was viewed until the late 1970s as a process to make sure the programme met the requirements. After then, in addition to making sure the software was running properly, it was expanded to detect the faults. The testing process was also thought of as a way to gauge quality in the 1980s. As a result, it was given more significance and was handled as a process that was part of the software development life cycle and was explicitly defined and monitored. The testing procedure established its own life cycle by the middle of the 1990s.

Better understanding of software cost estimate is required to improve the realism of software development project bids and budgets. Instead of generic software development, we wanted to see empirically supported methods for estimating software effort costs, but the research turned up only standard COCOMO models, function points, expert judgments, and a few formal models that had already been established, indicating their maturity in both academia and industry.

The research is devoted to a single, unified vision for empirically based software effort cost estimation in testing, which is not addressed by the articles, publications, research, and studies. The documents a huge set of publications, innovations, and advancements in evidence-based assessment of software cost effort in verification, validation, and testing are systematically analysed through study reviews, which are crucial for their systematic analysis. Evidence-based software engineering (EBSE) is a branch of science that collects data from real-world industrial settings in order to determine the likelihood of study outcomes. Despite not always reflecting the actual practise environment, random controlled experiments are also evidence-based.

The Evolution of Software Testing

In early days of software development, software testing was considered only a debugging process for removing errors after the development of software.

We can divide the evolution of software testing into the following phases;

Debugging oriented phase
Demonstration oriented phase
Destruction oriented phase
Evaluation oriented phase
Prevention oriented phase
Process oriented phase

Debugging oriented phase:-

This stage represents the initial testing phase. The fundamentals weren’t recognised back then. Programmers wrote programmes and then tested them until they were certain that all flaws were fixed. Checkout, a word for testing that concentrated on getting the system to function, was used.

Demonstration oriented phase:-

In this stage, debugging kept going. It is understood in 1957 that the goal of checkout is not only to execute the software but also to show that it complies with the stated criteria. As a result, the range of the programme check-up expanded from programme runs to programme accuracy.

Destruction oriented phase:-

Here, the definition of testing was altered to “testing is to detect more and more errors” rather than “testing is to prove the absence of errors.” In this stage, the value of early testing was also recognised.

Evaluation oriented phase:-

In this stage, emphasis is placed on software product quality so that it can be assessed at every level of development.
When compared to issues discovered during the implementation or post-implementation phases, it was less expensive to troubleshoot problems that were discovered early in the development process.

Prevention oriented phase:-

The evaluation model stressed on concept of bug prevention as compared to earlier concept of bug-detection.
With the idea of early detection of bugs in earlier phases, we can prevent the bugs in implementation.

Process oriented phase:-

In this stage of the software development life cycle, testing was developed as a full procedure rather than a single stage (executed after coding)
The testing procedure begins as soon as a project’s requirements are established and proceeds concurrently with the SDLC (Software Development Life Cycle)

Software testing 1.0:-

In the SDLC, software testing was only seen as a single phase that came after coding. There was no test organisation. There were a few testing tools available, but their usage was restricted by their high price.
There was no high standard.

Software testing 2.0:-

Software testing started to take centre stage in this phase of the SDLC, and early testing became a thing. Numerous testing tools were also available at this time since testing was moving toward resource planning.

Software testing 3.0:-

Software testing is now evolving into a procedure that is focused on strategic effort. It implies that there should be a procedure that provides us with a general roadmap for the testing process. Goals for quality should be the driving force. In this phase, management is actively involved.

Software Testing Epoch:-

During this time, development and testing were viewed as mutually independent tasks. The testing team received the programme after it was finished and verified it. During the requirement analysis phase, testers were not very actively involved and only sometimes interacted with business stakeholders. They were primarily reliant on information that was imparted to them through documentation created during design and development or learning from programmers who developed the code.

The testing team’s adoption of restricted testing methodologies was a result of their lack of understanding of the needs and expectations of the clients. Based on their comprehension of the documentation, the testers would create a test plan and conduct ad-hoc testing of the programme. It is clear that there were certain restrictions, and the testing was not exhaustive. Testing developed, and the next phase was the period of exploratory and manual testing.

Manual Testing and Exploration:-

Agile testing, exploratory testing, and other approaches became popular in the late 1990s. Manual testing was carried out with the use of thorough test designs and test cases. By examining the programme within the scope of testing charters, exploratory testing allowed users to test and break software in their own unique ways. The software development process needs more sophisticated testing methods due to its rapid and extensive growth. Agile testing’s gradual and iterative methodology contributed to the accomplishment of this objective. The repetitious tests those were able to be automated thanks to iterative testing.

The Age of Automation:-

Numerous fresh ideas that emerged with the turn of the millennium completely transformed software testing. These methods completely altered how testing was done. The SDLC was now considered to include testing at every stage. Quality control and assurance have become more important at every stage.

Automation raised the bar for testing significantly. The testers were further given the tools they needed to do their duties more effectively thanks to the abundance of automated testing frameworks. Automation made it possible to quickly and accurately carry out sanity and regression tests.

The testing procedure needed to be scaled up throughout this time period as well. The firm was able to manage product testing more quickly and with less infrastructure expenditure thanks to crowdsourcing and cloud testing.

The Continuous Testing

Customers now anticipated seeing an early functioning prototype of the finished product as the business dynamics started to shift. As a result, there was an increase in demand for regular and basic software releases. High connection and faster testing and deployment times across many platforms were made possible by enhanced network infrastructure.

This made delivery more frequent, which unintentionally resulted in additional testing effort. Continuous Integration and Continuous Deployment become well-known concepts. Continuous testing also acquired significance along with these. Shorter delivery cycles resulted from the rise of DevOps and CI/CD. It became essential to carefully evaluate threats in real time. At every level of the software development life cycle, risk assessment and management were required.

The business stakeholders expected intermediate releases under strict deadlines without sacrificing the final product’s quality. Continuous testing required to advance to become more effective in order to keep up with these expectations. This is where utilising artificial intelligence in testing comes into play.

A New Age of Artificial Intelligence:-

Artificial intelligence, put simply, is the ability of a computer to mimic human behavior through perception, comprehension, and learning.

The predictive analysis of data serves as the foundation for AI systems. This also implies that data is crucial for AI testing.
Today, a variety of testing solutions driven by AI are available to assist with unit testing, API testing, UI testing, etc. Visual testing is a prime illustration of how AI is used in testing.

What is Test Estimation?

For a specific software testing project in a specific environment utilising certain methodologies, tools, and techniques, test estimation is the estimation of the testing size, testing effort, testing cost, and testing timeline.

1. Estimation, which was previously defined in the topic
2. Testing Size – The quantity (amount) of testing that must be done. Sometimes, especially in embedded testing (where testing is integrated into the software development activity itself), this may not be estimated.
3. Testing Effort – The number of person days or person hours required to carry out the tests
4. Testing Cost – the costs associated with conducting tests, including the cost of human labour
5. Testing Schedule – the number of days or months in a calendar year required to conduct the tests.

Conclusion

Because it depends on the complexity and efforts employed for the specific product, the effort calculator is crucial for cost prediction as well as the ratio of testers to developers. The amount of time the product takes also matters a lot. Nowadays, automated and AI-based testing is a common technique, but as my research shows, all modern techniques are based on manual testing.

To overcome the problem of software test effort estimation Testbytes creates a test effort calculator for cost estimation, which is used to estimate the amount and time frame required for testing your software. The Testbytes software test effort calculator is designed for specification and user preferences.

The test cost calculator has many domains, such as banking and finance, telecom, e-commerce, etc. The cost calculator is platform-independent, i.e., you can select web, mobile, or both platforms at the same time. The total number of testing cycles required for the entire process determines the final cost.

What is the Optimum Software Developer to Software Tester Ratio?

Posted on December 5, 2022 by tbsupadminnxtbackendacc

How many testers are required to test a product? This seems like the start of a comedy, yet it’s a serious question. Quality assurance is an essential job, especially in today’s age of “release early, release frequently.”

People look for quality in every piece of art they come across. Quality has also invaded the realm of software development, where it is critical to properly test the software system at various stages of testing. Nowadays, competition is fierce and the frequency of changes in platforms and business needs is also significant. So, for a programme to be reliable and useful in the long term, it must be supported and updated depending on current requirements.

Software testing is one of the major tasks undertaken at every firm to deliver value and quality, as well as to assure the marketability of software products.

A variety of things influence what a decent tester-developer ratio should be. Consider whether you are working on cutting-edge technology or a legacy product, your team members’ ability and experience, and the release cadence you are required to maintain. The reality is that there are several ratios that may be used, but each has advantages and disadvantages.

Why should you employ a developer-to-tester Ratio?

These questions can aid in determining the testing process’ balance and efficacy. It may be better to utilise the developer-to-tester ratio as a matric to alter the testing process and workload in a test organisation rather than to estimate staffing levels before making team sizing decisions based only on numbers of people.

Let’s start with a developer-to-tester ratio examples.

Tester: 1 Developer

When you have developers who don’t know much about testing and testers who don’t know much about development, the 1:1 ratio is ideal. A developer and tester team can collaborate to deploy a new feature, and since they are both so focused on that one item, they may be able to uncover and solve all of the flaws. The developer, on the other hand, is unlikely to contribute to any test automation, and the tester is likely to be the only one who understands how to run and repair the automation. This means that if the feature is ever developed further, the tester will become a bottleneck, slowing down the job.

1 Tester: 2 Developers

This ratio is appropriate for a feature that requires both front-end and back-end development. The tester may be in charge of testing the integration of the front and back ends. These three, like the 1:1 ratio, will become the feature’s specialists. However, this might lead to silos, making it impossible for someone else to come in later in the project and assist with the task.

2 Testers: A team of Developers

This is a pretty regular occurrence. The testers can split the tales to be tested based on their skill set and availability. If both testers are competent and organised, they should be able to keep up with both manual and automated testing. They can also trade features to determine if one tester missed an issue discovered by the other. This ratio, however, can occasionally result in bottlenecks when a product requires extensive testing or when one tester is on vacation.

1 Tester: A development team

In this case, the tester takes on the role of “quality coach.” They are not in charge of all of the testing or test automation. They advise and coach developers on what should be tested and automated. Quality is thus owned by the entire team. When the tester is unavailable, the developers can fill the void by making test plans and checking each other’s work. Because developers contribute to and assist maintain the automated tests, test automation is never a bottleneck.

0 Testers: A development team

Some may squirm at the thought, but a team of highly skilled software engineers is capable of performing all of their own testing. To be successful, developers must grasp the value of exploratory testing and how to design test strategies. They must understand what kind of tests should be automated and they must commit to maintaining their test code with the same care that they do for their production code.

Although they will do preliminary testing on their own features, they will also form “test buddy” pairings in which one developer will act as the tester for the work of another developer.

They will have two sets of eyes on each feature and will be more likely to catch bugs this way. These ratios all share a few characteristics. First and foremost, at least one member of the team must be an expert in testing. These abilities are required to locate elusive bugs.

Following that, effective communication skills are required. There is no “throwing software over the wall to be tested.” Instead, testers and developers collaborate. Finally, there is the willingness to work as part of a team. Both testers and developers must be willing to step up and perform testing duties, whether or not it is part of their allocated function. When all three of these elements are present on a team, any of these ratios can lead to success.

Discussion

The tester-to-developer ratio varies slightly depending on estimated costs. The cost estimation is primarily determined by the type of firm client; it will differ for various service providers, such as healthcare, e-commerce, the automation industry, and so on.

The effort calculator plays an important role for the estimation of cost as well as the ratio of the tester to developer because it depends upon the complexity and efforts used for the particular product. The time consumed by the product also plays a key role.

To roughly estimate the number of testers required for future projects, the ratio of testers to developers on previous projects in a well-known domain can be utilised in conjunction with a study of impacts on the relative number of testers vs. developers. When details about the functioning and features of the proposed project are unknown, or when a rapid estimate is required but a wide margin of error is allowed, this technique is most helpful.

Conclusion

The developer-to-tester ratio varies greatly amongst companies. The term “industry average” may not even be a reasonable starting point. This measure may be more useful in enhancing your testing procedure than in hiring your team. With the correct mix of people, tools, and procedures, you can execute effective testing even in high-ratio circumstances.

The balance also varies based on the company’s present stage. In the early stages of a software startup, the focus is on prototyping, hacking, and generating tested minimum viable products rather than production level development. When the entire workforce is less than five full-time equivalents, they may do without a specialised software quality assurance department and spread the load of testing their programme between themselves and their early customers/ testers.

It is difficult to explain the tester-to-developer ratio because each company’s position and requirements are unique and dependent on their needs. basically the ratio is dependent upon the complexity of a particular product, and no interface is established to give an accurate number for the ratio. Testbyte proposed a cost calculator that is useful for everything related to software development and testing, providing cost estimation, tester-to-developer ration, and total time required to complete the product or task.

In conclusion, estimating testing based on ratios of testing to development workers is a problem that cannot be solved and any organisation that is presented with such a solution should seriously consider its validity.

How to Outsource Website Testing Services?

Posted on November 29, 2022 by tbsupadminnxtbackendacc

Before we go into why website testing is being outsourced, let’s look at what this entails. Outsourcing is an agreement made by one company with another for website testing.

There are some best practices expected by clients who outsource website testing.

1. Clarify the needs:

Outsourcing website testing needs a clear work scope. If your customer does not offer them, you must define and explain the needs. Don’t put it off; make it simple for the client to work with you. Both parties should evaluate the scope on a regular basis to ensure that there are no disputes or misunderstandings.

2. Create a sense of collaboration with the customer:

Make yourself a member of the client’s team, not a remote add-on. Know who the players are, what their habits are, and when they will evolve so that you can fit into their processes. Harmonize with the development team, follow their rhythm, and accept their vision.

3. Make use of varied time zones:

Assume the developers are in the United States and the testers are in Europe. After coders in America finish their job for the day, they may send their build to testers in Europe, whose day begins hours later. Use the time overlap to connect while taking advantage of your clients’ leisure to get a lot of work done and show them the results the next day.

4. Enhance communication:

To eliminate knowledge asymmetry, timely communication is necessary when outsourcing website testing. Many technologies, such as instant chat (Google Talk, MSN), email or SMS, shared documents and dashboards, problem tracking systems, configuration management tools, screen sharing, and so on, can be employed. Before the project begins, both parties should agree on the communication routes.

5. Be flexible and adaptable:

Each company has its own workflow and methods. As an outsourced website testing services firm, we adhere to our customers’ QA protocols, which necessitates the use of adaptable teams. When working with a new client, the outsourced QA testing team should be able to swiftly learn new workflows and the testing process, as well as adapt to a new work style.

6. Recognize your customer’s cost structure:

Your client is outsourcing website QA to you because you can deliver a service at a lower cost than they could if they performed it themselves. Perhaps you are giving skills that would be too expensive to acquire and bring in-house. Understanding the specific scenario for each of your clients can help you determine whether you are pricing yourself out of a project or whether there is a broader area of services for you to supply.

7. Emphasis the need of effective written language skills:

English is the worldwide business language. English is frequently the second language of both the customer and the outsourced team. This can be difficult when conversing often via email. One of the most critical criteria for project success is smooth and effective communication between the customer and the outsourced QA team in charge of testing. Make certain that your communication is succinct, thorough, and correct.

8. Be the authoritative figure:

Be the expert in the area where the client wants you to be an expert – quality assurance and testing. Be or become a domain specialist, such as one in financial software. Highlight your expertise and ability to apply it to completely evaluate your client’s goods. Finally, become a specialist in the client’s unique application.

9. Make yourself visible:

Lack of visibility with key executives in your customer’s organisation may be terrible since you want your worth to be recognised throughout the client. It may be challenging to gain higher awareness as the single member of the outsourced QA testing team. First, identify important managers and provide them with regular updates, statuses, and outcomes (particularly if they are positive). Visit the client and make a point of seeing and speaking with those important managers, even if just for a few minutes.

10. Establish communication priorities:

Although most of the items on this list imply it, it cannot be overstated. Communicate with a goal in mind. Don’t just bombard your customer with information. Selective communication is required. Ensure that the appropriate information and analysis are sent to the appropriate individual. A developer may value a great deal of technical detail, but the development manager is interested in timeline information.

Why outsource website testing is necessary?

Enhancing existing projects

If you want to test your own website, you may have no prior expertise or experience. As a result, hiring a website testing firm is the ideal option. In general, the most experienced of these organisations have gone through trial and error during their career in the sector and are continually analysing risks and errors and correcting them, which works in your favour when you hire them. They are capable of delivering the efficient outcomes you want.

Global economic disparities

Website testing costs far less in poor nations than in developed countries. You may employ a whole testing team from India or China at the same cost as hiring one or two testers in the United States or Germany. As a result, outsourcing website testing will help you save money.

Find the best candidate for the position

Your location, business size, and other factors all have an impact on the website testing constraints you encounter during a project. For example, you could wish to include one of the most recent technologies into your project. However, you may not be able to find somebody with relevant experience to assist you. Or perhaps you started a project, but were unable to complete it due to a lack of resources or experience. Outsourcing is useful in these instances. You may locate someone suited for the job from all around the world with the skills to complete your testing needs on time and within budget.

Task prioritisation

Prioritising jobs is an excellent approach to increase work productivity while also managing time so that all essential project activities are finished on time. Even if your team handles the majority of them, things like app development, marketing and other management activities may still require people. Outsourcing is the ideal answer in these cases.

Conclusion

Outsourcing the testing of any product is always a good alternative. It helps us concentrate on our core work and save time. Testing outsourcing allows us to prioritise tasks and achieve excellent milestones. Outsourcing is the best solution for testing in all types of development.

75 Must Read Test Lead Interview Questions

Posted on March 23, 2022February 8, 2024 by tbsupadminnxtbackendacc

Are you looking forward to the Test Lead interview you are going to attend? then you must have a look at our blog, 75 Test Lead interview questions For A better Job

Important Test Lead interview questions you must read first!

You will be asked about the project life cycle and development model that’s in practice your company
What’s going to be your action if management decided to approve a release with critical defects?
Why do you use the testing tools that you are using now?
How do you decide whether you have enough test cases to test a module
How do you test a search engine
Difference between UAT and system testing
How do you use selenium for code validation?
How do you reverse INT and double number?

Describe the key responsibilities of a Test lead.

Must be able to guide his team members, manage the tests team effectively, identify the scope of testing required and its related tools, and create a fun and learning environment for juniors.

Mention the key challenges of Software Testing.

Key challenges may include:

Testing phase under a time constraint
Regression Testing
The application must be stable to run tests
Lack of tools, resources, and training for the testers

Mention different types of testing methods.

There are 3 basic methods-

Black-Box Testing: No in-depth knowledge of internal paths, structures, or implementation is required.

White-Box Testing: Core and in-depth knowledge of internal paths, structures, and implementation are required.

, and Grey-Box Testing: Limited knowledge would suffice to detect and debug the software.

Difference between functional and non-functional testing.

Functional testing is done before non-functional based on the client’s requirements and describes what a product does. Non-functional testing is based on the client’s expectations and tells how the product works.

Mention the benefits of Automated Testing.

Cost-saving, fast Development, and Delivery of products, higher productivity, effective and efficient use of resources, support repeated test cases execution, improves accuracy.

What is usability testing?

It is a type of testing methodology where a user is asked to use the product to check whether the software is easy to use, its task loading time, and to understand the customer’s perception.

Describe how Testing is affected by Object-Oriented Programming.

Makes it easier for testers to trace the requirements from code to internal paths to functional designs.

How to use WebDriver for launching the different browsers?

A common syntax can be used;

WebDriver driver = new FirefoxDriver();

WebDriver driver = new ChromeDriver();

WebDriver driver = new InternetExplorerDriver();

List some best effective Software Quality Assurance practices.

It may include-

Unhindered improvement
Proper and precise documentation
Usage of best tools and resources

Describe the testing strategies you have found to be most effective?

Following are the testing strategies I have found to be the most effective ones to achieve the main objective:

Unit testing
System Integration Testing
Deployment Testing
Alpha Testing
Beta and User Acceptance Testing

What do you understand by Requirements Traceability Matrix?

RTA is a table format document required to determine the level of testing through relation comparison between two baselined documents and details the technical requirements for all applications fulfilled in the verification process.

Explain the types of test plans?

Some of the types are:

Level-specific test plans– it addresses any one phase of the testing approach
Specific Type test plans– it is designed for non-functional testing like security testing, loading testing, etc.
Master test plans– It’s a complete test approach

What is the difference between Verification and Validation in Software Testing?

Verification– It is a static testing process to check if the application achieves its goals without any bugs

Validation– It is a dynamic testing process to determine whether the product we are developing is the right product and meets the client’s requirements.

While running a test on a project, what are the risks to be avoided?

The risks can be categorized as-

Strategic Risks
Project Defining Risks
Human Resources Risks
Project Estimation and Scheduling Risks

What are the measures you have used against such risks?

The following can be practiced to avoid the risks-

Avoidance– Eliminate the possible risks

Reduction– Alleviate plan to mitigate the impact of the risks and take valid measures

Sharing– Outsource the risk to other resources

Acceptance– Accept and prepare the planned budget for the risks

What are the categories of bugs?

Three prime defects categories are-

Wrong- It states that requirements are varying from the given specifications.

Missing- it implies that a specification isn’t implemented or noted properly.

Extra- It indicates a requirement has been implemented into the product that wasn’t given by the client.

What are the practices you have used to minimize the impact of defects?

Discover the type of defect
Prioritize the categories of defects to simplify the tasks
Get the skilled developers to fix the defects
Verification process by testers
Once resolved and verified, change defect status to closed
Prepare and send the defects reports to a management team for feedback

How can you arrive at a test estimation on a project?

The answer to the ‘how’ part involves-

Create basic test scenarios

Get an idea of the number of test cases to work on

Include buffer time

Identify their complexities

What is a Three-point estimation?

It is a technique used to determine the approximate profitable distribution that defines the outcomes of future events. Three-values can be determined by-

Best case estimate
Most-likely estimate
Worst-case scenario estimate

What are the stages involved in the software testing life cycle?

Following are the STLC phases one should consider-

Product requirement analysis
Test planning
Prepare test case development
Set up a testing environment
Execute testing on the prepared test cases
Test closure

What steps do you follow to create a test script?

There are three ways you can test script-

Record/playback by writing any code in a simplified language like VBScript
Keyword or data-driven test scripting
Writing code using Programming Languages like JScript, Ruby, Java, etc.

What do you understand by PDCA and how do you use it?

it is a Test Process Involvement Method explained for Plan, Do, Correct and Act and is used to help testers improve future processes and strategic implementation.

What is test coverage and its types of techniques?

It is a parameter used to describe the scope of source code testing. The basic techniques include- Statement, Decision, and path coverage.

Describe Manual Support and Manual Scripted testing.

Manual Support testing– It is a process where a QA analyst manually executes the test cases to identify bugs and generate reports.

Manual Scripted Testing- It involves 3 steps- Execution, Reporting, & Information. This sequential method is used to review and design the test cases before executing them.

On what grounds can you map the success of Automation testing?

It can be mapped by-

Detecting defects ratio
Automated testing execution time
Assign professionals
Reduction in costs where possible

Name the commonly used Automation Testing tools.

Some of the tools are- Selenium, Appium, Katalon Studio, Cucumber, HPE UFT, SoapUI, TestComplete, QA Wolf, and much more.

How to select a testing tool?

Understand the project requirements, Use your current testing tool as a standard one, Determine salient criteria suitable for the product.

Name the test cases that can be automated.

Smoke test, Regression Test, Data-driven, Non-functional, and Complex Calculation test cases.

Difference between Regression and Confirmation testing.

Regression Testing– To ensure that a change in recent code doesn’t affect existing characteristics.

Confirmation Testing– Or re-testing is a process of introducing a new version of software whose defect is fixed.

What is BVA?

Boundary Value Analysis is a black-box testing technique used to check whether there are any bugs at the edge of the input domain.

What should a good test report include?

Detailed project information, test objectives, and classifications explained test briefly, and defect reports if any.

What are the basic defect report format components?

They may include- Project name, module name, defect detected on and by, Unique Defect ID and Name, defect snapshot, Priority and Severity status, Defect resolved on and by.

Compare Agile Testing with Traditional testing?

Traditional Testing follows a phased testing approach where unit testing is performed for each module without any tools. It is time-consuming and more costly. Agile Testing follows an iterative approach along with an adaptive model where the bugs are fixed during testing using automated tools and then released.

What is the command to click on hyperlink using linkText()?

The command is as follows-

driver.findElement(By.linkText(& ldquo; Google& rdquo)).click();

What is Defect cascading?

When a defect goes unnoticed while performing tests it invokes other defects due to which multiple defects arise in the later stages.

What method to use when there is no frame id and frame name?

If such the case is, we can approach fame by index. The syntax would go like this-

driver.switchTo().frame(int arg0);

Mention a difference between Beta and Pilot Testing.

Beta Testing is User Acceptance Testing which is performed in the development environment after the product launch to minimize the failure risks. Pilot testing is done before launching a product in a real environment.

Describe Configuration Management.

It determines the tools, including source code, test scripts, hardware, third-party software, and development and testing documentation to establish the consistency of a product.

What would be your strategy if you find that the testers in your company are performing deliverables even after a potential defect has been detected?

The acceptance pattern should be strict, test cases must be revised and added more to check the ineffectiveness, and the show-stopper bar should be improved as compromising the company’s quality is not acceptable.

What is Load Testing on websites?

The QA engineers need to multiply the number of responses a user is getting when sending a request to that site’s server to simulate different traffic loads.

Describe TestNG.

It is an advanced testing framework designed with an inbuilt exception of handling mechanism which helps the program to run without terminating suddenly.

How will you skip a method or a code block in TestNG?

We can set the ‘enabled’ parameter in test observation to false using the below format-

@Test(enabled=false)

How would you find out the quality of the test execution?

There are two ways to determine it-

Defect Rejection ratio: (No. of defects rejected/total no. of defects raised)*100
Defect Leakage ratio: (No.of defects missed/total defects of software)*100

Acceptance plan is prepared on what basis?

Requirement documents, input from the customer, and project planning determine the acceptance plan.

Describe XPath.

Also known as XML Path is a language to query XML docs. One can easily write a query in XPath script to locate elements in a webpage. It also generates reliable locators.

What is Absolute Xpath?

It is a better and more direct way to find the element but if you make any changes in the path of the element then that XPath gets failed. For instance, /html/body/div[1]/section/div[1]/div

What is Relative XPath?

The path starts from the middle of the HTML DOM pattern and begins with the forward double slash (//) which signifies that you can search the element anywhere on the webpage.

How will you handle the conflicts between teams?

Since the team members are from diverse backgrounds and different working styles, the key step as a Team Manager would be open communication for all to understand better and work together which also minimizes the frustration within the team.

What are the skills required to be a test manager?

A positive and practical approach, maintain a decent relation with fellow workers and motivate them, a leader with a creative and problem-solving attitude and understand the priorities when working.

What do you expect while working with us, if hired?

A friendly yet professional, positive work environment, flexible working hours that your Company offers, job stability, and an opportunity to grow and hone my skills with the company.

51. How do you handle a situation where there is a conflict between the testing team and the development team?

Effective communication, collaboration, and understanding each other’s perspectives are key to resolving conflicts.

52. Can you explain the importance of test data in the testing process?

Test data is crucial for validating the functionality of the application under various scenarios and conditions. It helps ensure comprehensive test coverage.

53. What are the key factors to consider when creating a test environment for a project?

Hardware and software compatibility, data availability, network configurations, and cloning production environment are essential considerations.

54. How do you prioritize test cases when time is limited?

Prioritization is based on risk, critical functionality, and business impact. Focus on high-priority areas to ensure the most critical aspects are thoroughly tested.

55. Explain the concept of continuous testing in the software development life cycle.

Continuous testing involves automated testing throughout the development process, ensuring quick feedback on code changes and maintaining software quality.

56. What role does exploratory testing play in your testing strategy?

Exploratory testing is used to discover defects in an unscripted manner. It complements scripted testing and helps identify issues that might be missed in traditional testing.

57. How do you keep your testing team motivated during a challenging project?

Motivation comes from recognizing achievements, providing a positive work environment, and addressing team concerns promptly. Regular feedback and acknowledgment are essential.

58. Can you share an example of a successful test automation implementation in a project?

Describe a scenario where test automation significantly improved efficiency, reduced testing time, or enhanced test coverage in a project. Quote such instances from your personal experiences. Be prepared with a couple of such scenarios.

59. What strategies do you employ to ensure effective communication within the testing team?

Regular team meetings, clear documentation, and utilizing collaboration tools can facilitate effective communication among team members.

60. How do you ensure that the testing process aligns with the project timeline?

Thorough planning, realistic estimations, and continuous monitoring of progress are essential to ensure that testing activities stay on track with the project timeline.

61. What steps do you take to stay updated with the latest testing tools and technologies?

Regularly attend conferences, webinars, and workshops, subscribe to industry publications, and encourage team members to share knowledge on emerging trends.

62. Can you explain the significance of risk-based testing in the testing life cycle?

Risk-based testing involves prioritizing test cases based on the likelihood and impact of failure, ensuring that testing efforts focus on areas with higher risks.

63. How do you handle testing in a project with frequent changes in requirements?

Agile testing methodologies, continuous collaboration with stakeholders, and maintaining flexible test cases are crucial in adapting to evolving project requirements.

64. Describe a situation where you had to make a tough decision as a Test Lead. How did you handle it?

Provide an example of a challenging decision you made, the factors considered, and the outcomes, showcasing your leadership and decision-making skills. Always make sure to be prepared to answer such personal experiences based questions before going for an interview.

65. What strategies do you employ to foster a culture of continuous learning within the testing team?

Encourage team members to participate in training programs, allocate time for skill development, and promote knowledge sharing within the team.

66. How do you ensure that test cases are reusable for future projects?

Designing modular and well-documented test cases, using automation frameworks, and maintaining a centralized repository of test cases can contribute to reusability.

67. Can you explain the role of risk analysis in test planning?

Risk analysis helps identify potential challenges, prioritize testing efforts, and allocate resources effectively to areas with higher risks in the test plan.

68. Describe a scenario where you had to deal with a critical production issue related to testing. How did you handle it?

Share an experience where you addressed a critical issue affecting production, emphasizing your problem-solving and crisis management skills.

69. What metrics do you use to measure the effectiveness of the testing process?

Metrics such as defect density, test coverage, and test pass rate can be used to evaluate the effectiveness of the testing process.

70. How do you ensure the security testing of an application is comprehensive?

Comprehensive security testing involves identifying potential vulnerabilities, implementing penetration testing, and staying informed about the latest security threats and measures.

71. Can you discuss the role of test documentation in ensuring the traceability of testing activities?

Test documentation, such as test plans and test cases, plays a crucial role in tracing testing activities back to project requirements, ensuring thorough coverage and validation.

72. What measures do you take to ensure the confidentiality of sensitive data during testing?

Implementing data masking techniques, securing test environments, and establishing strict access controls are crucial to safeguard sensitive data during testing.

73. How do you handle a situation where a critical defect is discovered late in the testing process?

Address the importance of effective communication with stakeholders, assessing the impact, and collaborating with the development team to expedite the resolution.

74. What strategies do you employ to ensure test coverage for mobile applications across various devices and platforms?

Utilizing mobile testing frameworks, leveraging cloud-based testing services, and maintaining a diverse device and platform matrix contribute to comprehensive mobile test coverage.

75. Can you share an experience where your testing efforts contributed to significant cost savings for the project?

Highlight a situation where thorough testing prevented the identification of defects in later stages, resulting in cost savings for the project.

All the best!

Hope you liked our compilation of Test Lead interview questions. We wholeheartedly wish you all the best for your future.