55 Funny Programming Memes That Testers Would Love!

Are you feeling the weight of a thousand “critical” bugs on your shoulders? Does the phrase “release deadline” send shivers down your spine? Worry not, brave test warriors! We’ve all been there, wading through lines of code and user reports like intrepid explorers in a digital jungle. But fear not, for we have a secret weapon in our arsenal: laughter.

Join us on a journey through 75 hilarious programming memes, curated specifically to melt away your stress and remind you that even in the face of the most baffling bug, sometimes, all you need is a good chuckle to keep going.

How Does Meme Help? :p

  • The “Works on My Machine” Defense Shield: When the devs swear their code is flawless, only to unleash buggy chaos on the world, testing memes is the ultimate comeback weapon.

  • The Sanity Preservation Kit: Let’s face it, finding a bug that could crash civilization is stressful. Memes permit us to laugh at the absurdity of it all, keeping our brains from short-circuiting.

  • The Universal Language of Frustration: That moment when a test fails for the 99th time, and only a meme can accurately express your exasperated soul.

  • Comradery Within Chaos: Sharing testing memes builds a secret society of those who understand the struggle. It’s like, “Yep, you also spend hours chasing a bug that resulted from a single misplaced semicolon? We’re in this together.”

  • Reminder That Bugs Are Hilarious (Sometimes): When faced with software so broken it’s comical, a good meme turns that frustration into entertainment. After all, if we can’t laugh, we’ll cry.

#1) Don’t stress! Others won’t get it!


#2) S#$% happens!

 #3) Hmmmmmmm



#4) Been there done that

#5) Hell Yeah!

#6) Haaa!

#7) No pun intended

#8) Lel

#9) Did I write this?


#10) We are the same



# 11) Time flies

#12) Hail the anchorman!

13) That hurts

#14) Destiny is pre-written

#15) Do not take it off

#16) Yup! We’ve all been there.

software testing requirement meme
#17) Think about it

#18) I’m god!

#19) That’s clever

#20) Awwwwwww

#21) Die!

#22) Enjoy

#23) The Real MVP

#24) What’s that?

#25) Never, ever

#26) We don’t do that

#27) Chuck Norris it is!

 #28) It’s a War every day

#29) It’s over the kid

#30) Darth Vader is right!

#31) We have your back, but beware 😛

#32) Wait a second

#33) Just Python Things

#34) Requirements

#35) But the emote is different you know

#36) A win is a win

#37) Indeed!

#38) Now I get it

#39) Cliché but true

#40) Am I a joke to you?

#41) That’s deep yo

#42) Kill me pleezzzz

#43) Yeah we do time travel too

#44) Huh?
#45) How cool is that B-)   
#46) Nooooooooooooooooooooooooo

#47) 😛

#48) It didn’t last long L

#49) Lannister is wise

#50) xD


#51) Well……


#52) Why? Why? Why?

Programming Memes for Testers #52



#53) Haa Regression, Regression

Haa Regression, Regression


#54) Ahaaaaa



#55) The UI testing conundrum


The UI testing conundrum


If you wish to laugh more, here’s a link to the subreddit



Manual Software Testing Services – Why Testbytes Stand Out!

In today’s digital landscape, quality software isn’t a luxury; it’s a necessity. While automation is crucial, manual testing remains an indispensable pillar of Quality Assurance (QA). A recent World Quality Report (2023-24) found that 73% of businesses aim for a balanced testing approach, integrating manual and automated methods. The reason? Manual testing’s unique strengths.

Testbytes adopts a unique manual testing methodology that stands out in the industry. Our approach integrates traditional testing techniques with innovative strategies to enhance accuracy and efficiency in identifying bugs and usability concerns. 

By prioritizing user-centric scenarios, Testbytes ensures that applications are technically sound, intuitive, and engaging for end-users. This holistic approach underscores the importance of manual testing in delivering high-quality software products in today’s digital landscape.

Testbytes Manual Testing Process 

  • Requirement Analysis: The process begins with in-depth software requirements analysis. Testers gain an understanding of the functional and non-functional aspects of the application to ensure comprehensive test coverage.
  • Test Plan Creation: A test plan is developed based on the requirement analysis. This document outlines the strategy, objectives, schedule, resource allocation, and scope of the testing activities.
  • Test Case Development: Testers create detailed test cases that include specific conditions under which tests will be executed and the expected results for each condition. This step is crucial for systematic testing and covers various aspects such as functionality, usability, and performance.
  • Test Environment Setup: The necessary testing environment is set up before executing the test cases. This includes configuring hardware and software requirements that mimic the production environment as closely as possible.
  • Test Execution: Testers manually execute the test cases and document the outcomes during this phase. They compare the actual and expected results to identify any discrepancies or defects.
  • Peer Testing (Added Step):
    • Integration into Workflow: After individual test case execution, peer testing is introduced as an additional step. This involves having another tester, who did not originally write or execute the test case, review and re-run the tests.
    • Benefits: Peer testing brings a fresh perspective to the testing process, often uncovering issues the original tester might have overlooked. It enhances test coverage and accuracy by leveraging the collective expertise of the testing team.
    • Execution: Testers can perform peer testing in pairs or small groups, discussing findings and insights collaboratively. This step encourages knowledge sharing and can lead to more innovative testing approaches.
  • Defect Logging and Management: Any defects found during test execution and peer testing are logged in a tracking system. This includes detailed information about the defect, reproduction steps, and severity level.
  • Test Closure: The testing process concludes with a closure report summarizing the testing activities, coverage, defect findings, and an overall assessment of the application’s quality. This report helps stakeholders make informed decisions about the software release.

Manual Testing Process

Our Creative Approach Towards Manual Testing

Creating Charters and Use Cases from Requirements

We begin by translating the project requirements into detailed charters and use cases. This approach ensures a comprehensive understanding of the application’s expected functionality and user interactions. For each use case, identify the actors involved and outline their impact on the system and the expected outcomes. This methodical preparation lays a solid foundation for effective testing.

Utilizing Exploration Strategies and Guiding Principles

Implement exploration strategies and guiding principles in software testing to direct the execution of test charters. 

Similar to simulated user journeys or focused feature investigations, exploration strategies reveal defects that formal testing methods may overlook. Guiding principles, akin to practical wisdom or best practices, assist testers in efficiently traversing the intricate software environments. 

Distribute a weekly agenda among the team members, detailing the specific exploration strategies and guiding principles to be applied, promoting a unified approach and cooperative endeavor toward enhancing product quality

Applying IPSOVI in Manual Testing:

The IPSOVI technique offers a structured approach for manual testing, covering every software aspect: Input, Process, Storage, Output, Verification, and Interface.

Testers identify inputs, assess processing logic, examine data storage, validate outputs, check verification mechanisms, and test interfaces for external communication. 

This comprehensive method involves creating specific test cases, executing them to observe application behavior, and systematically documenting defects related to IPSOVI components. 

Collaboration and review with the development team ensure thorough coverage and improvement. 

Applying IPSOVI enhances software evaluation, leading to more reliable, high-quality applications by ensuring all critical areas are rigorously tested and validated.

Enhancing Manual Testing with Visual Validation Tools

Visual Validation Tools revolutionize manual testing by automating the visual comparison of applications across devices and platforms, ensuring UI consistency and enhancing user experience. Here’s how they contribute technically:

  • Automated Screenshot Comparisons: Quickly identify visual discrepancies across various environments.
  • Cross-Platform Consistency: Guarantee uniform appearance on different devices and browsers.
  • Pixel-Perfect Validation: Detect minute visual deviations with precision.
  • CI/CD Integration: Incorporate visual checks into automated pipelines for early issue detection.
  • Focus on UX: Free manual testers to concentrate on subjective user experience.

Exploration Strategies and Guiding Principles

Mind Mapping Techniques in Manual Testing

Mind Mapping in manual testing enhances organization and creativity, offering a visual approach to test planning and execution. Here’s how it benefits the testing process:

  • Visual Test Planning: Create intuitive diagrams representing test scenarios, requirements, and strategies.
  • Enhanced Communication: Facilitate clear, visual communication among team members.
  • Efficient Test Case Design: Organize and develop test cases by visually mapping out application features and their interactions.
  • Improved Coverage: Identify gaps in testing by visually assessing coverage areas.
  • Quick Reference: During testing cycles, use mind maps as a dynamic, easy-to-navigate reference tool.

How Do We Do Manual Testing Ticket Management: 

Effective ticket management is crucial in manual testing to streamline issue tracking, resolution, and communication. By leveraging specialized tools and techniques, teams can enhance productivity and ensure software quality. Here’s how to approach ticket management in manual testing:

Centralized Ticketing System

  • Tool Integration: Adopt a centralized ticketing system like JIRA, Trello, or Asana to log, track, and manage defects. These platforms provide a unified view of all issues, facilitating better prioritization and assignment.
  • Features Utilization: Use tagging, statuses, and filters to categorize tickets by severity, type, and responsibility. This helps in quick navigation and the management of tickets.

Effective Ticket Logging

  • Detailed Reports: Ensure each ticket includes comprehensive details like reproduction steps, expected vs. actual results, and environment specifics. Attachments such as screenshots or videos can provide additional context.
  • Standardization: Develop a template or guideline for reporting issues to maintain consistency and clarity in ticket descriptions.

Prioritization and Triage

  • Severity Levels: Define and use severity levels (Critical, High, Medium, Low) to prioritize issue resolution based on impact and urgency.
  • Triage Meetings: Conduct regular triage meetings to review, assign, and re-prioritize tickets, ensuring that critical issues are addressed promptly.

Team Collaboration and Communication

  • Cross-functional coordination: Facilitate collaboration between testers, developers, and project managers within the ticketing system through comments, updates, and notifications.
  • Feedback Loop: Implement a feedback loop for resolved tickets, where testers verify fixes and provide feedback, ensuring issues are thoroughly addressed before closure.

Continuous Improvement

  • Analytics and Reporting: The ticketing system’s tools generate reports on common issues, resolution times, and testing progress. This data can inform process improvements and training needs

Manual Testing Ticket Management: Tools and Techniques

Effective ticket management is crucial in manual testing to streamline issue tracking, resolution, and communication. By leveraging specialized tools and techniques, teams can enhance productivity and ensure software quality. Here’s how to approach ticket management in manual testing:

Centralized Ticketing System

  • Tool Integration: Adopt a centralized ticketing system like JIRA, Trello, or Asana to log, track, and manage defects. These platforms provide a unified view of all issues, facilitating better prioritization and assignment.
  • Features Utilization: Use tagging, statuses, and filters to categorize tickets by severity, type, and responsibility. This helps in quick navigation and management of tickets.

Effective Ticket Logging

  • Detailed Reports: Ensure each ticket includes comprehensive details like reproduction steps, expected vs. actual results, and environment specifics. Attachments such as screenshots or videos can provide additional context.
  • Standardization: Develop a template or guideline for reporting issues to maintain consistency and clarity in ticket descriptions.

Prioritization and Triage

  • Severity Levels: Define and use severity levels (Critical, High, Medium, Low) to prioritize issue resolution based on impact and urgency.
  • Triage Meetings: Conduct regular triage meetings to review, assign, and re-prioritize tickets, ensuring that critical issues are addressed promptly.

Team Collaboration and Communication

  • Cross-functional coordination: Facilitate collaboration between testers, developers, and project managers within the ticketing system through comments, updates, and notifications.
  • Feedback Loop: Implement a feedback loop for resolved tickets, where testers verify fixes and provide feedback, ensuring issues are thoroughly addressed before closure.

Continuous Improvement

  • Analytics and Reporting: The ticketing system’s tools generate reports on common issues, resolution times, and testing progress. This data can inform process improvements and training needs.


Our methodologies are not just procedures; they are the blueprint for success in a digital age defined by user expectations and technological advancements. As we navigate the complexities of software development, our focus remains unwavering: to deliver products that exceed expectations, foster engagement, and drive success.

Don’t let quality be an afterthought in your software development process. Choose Testbytes for manual testing services prioritizing precision, user experience, and efficiency.

Contact us today to learn how our unique approach can elevate your software products, ensuring they are ready to meet the demands of today’s digital landscape. Let’s work together to create exceptional digital experiences that captivate, engage, and endure.

A Guide to Identifying and Recruiting/Hiring Top Software Testing Talent

Software bugs are an inevitable part of the software development lifecycle. However, their impact can be significant, leading to downtime, performance issues, security vulnerabilities, and ultimately lost revenue and customer trust.

Here’s a look at the latest data on the cost of fixing bugs in production in 2023:

Estimated Costs:

  • Globally: The total cost of software bugs is estimated to be $2.08 trillion annually, according to a study by the Consortium for Information and Software Quality (CISQ). This represents a significant increase from previous estimates.
  • United States: In the US alone, the cost of bugs is estimated to be $607 billion annually, according to Herb Krasner’s report, “The Cost of Poor Software Quality in the US.”
  • Per Bug: The average cost to fix a bug in production can range from $1,500 to $10,000, depending on the severity and complexity of the issue.

The Crucial Role of Software Testers

Preventing Bugs:

  • Identify & fix issues early: Skilled testers find bugs before release, saving time & money.
  • Extensive testing: Thorough testing across various platforms & scenarios minimizes issues.
  • Proactive approach: Early identification prevents major product failures & data breaches.

Cost Savings:

  • Reduced bug fixing costs: Finding problems early avoids expensive fixes later in development.
  • Downtime minimization: Fewer bugs mean less downtime and lost revenue.
  • Enhanced product quality: Improved software leads to higher customer satisfaction and loyalty.

Brand Protection:

  • Minimized security risks: Effective testing detects and mitigates security vulnerabilities.
  • Reputation management: Quality software protects your brand image and builds trust with customers.
  • Increased customer satisfaction: Bug-free software leads to a positive user experience and brand reputation.

Additional Benefits:

  • Improved software functionality: Testing ensures features work as intended and meets user needs.
  • Enhanced development efficiency: Early bug detection reduces rework and streamlines development.
  • Competitive advantage: High-quality software provides a competitive edge in the market.

The Global Hiring Dilemma: Finding Top Software Testers

Employers around the world are finding it extremely difficult to locate and hire qualified software testers. This hiring conundrum affects companies of all sizes and sectors; it’s not just a minor inconvenience.

For instance, the growth of fintech. Just take a look at the fintech industry. The need for qualified testers to verify the stability and security of cutting-edge financial apps and platforms is growing. However, the small pool of competent testers is finding it difficult to keep up, which could result in security risks, delays, and compromises.

Real-World Difficulties:

  • Skill Gap: There is a discrepancy between testers’ current skill set and what the industry needs because of how quickly technology is developing.
  • Competitive Environment: Renowned tech firms and upstarts are fiercely competing for the same talent, driving up wages and making it harder for smaller businesses to survive.
  • Geographic Restrictions: In emerging markets or remote areas, traditional hiring practices frequently restrict access to a wide range of talent pools.

Beyond Boundaries: Investigating Remedies:

Businesses are currently looking into a number of options to get past the hiring conundrum, such as:

  • Outsourcing: You can get access to qualified workers at reasonable prices by collaborating with specialized testing companies in nations with robust labor pools.
  • Upskilling and Reskilling: You can close the skill gap and build a pool of future testers by funding internal training initiatives or partnering with academic institutions.
  • Hiring remotely: By adopting remote work policies, businesses can access a worldwide talent pool without regard to location.
  • Emphasizing Soft Skills: Although technical proficiency is essential, employers are increasingly seeking testers with strong interpersonal, teamwork, and problem-solving abilities.

A Collaborative Approach:

The global software testing landscape faces a crucial challenge: a limited talent pool against a rising demand for skilled testers. To address this, a collaborative approach is necessary, involving different stakeholders within the SDLC. This includes fostering cross-team communication for joint test planning and execution, promoting shift-left testing, and sharing knowledge and skills between developers and testers.

Additionally, collaboration with academic institutions can ensure industry-aligned curricula, internship opportunities, and research partnerships. Furthermore, government bodies can incentivize training programs and promote international cooperation. By embracing this collaborative approach, we can build a future with readily available skilled testers, contributing to higher quality software, enhanced customer satisfaction, and a thriving global market

Introducing Testbytes: Your Strategic Ally in Talent Acquisition and Staffing Solution

At Testbytes, we redefine the landscape of software testing talent acquisition. As a distinguished leader in the industry, our mission is to empower businesses with the right testing professionals seamlessly and efficiently.

Why Testbytes? We pride ourselves on being at the forefront of providing innovative staffing and hiring services for software testers. Our commitment to excellence is reflected in our flexible staffing options tailored to meet the unique needs of your organization. Whether you require testers on an hourly, weekly, or monthly basis, Testbytes is your go-to partner for customized solutions.

QA Stafing and hiring process

Flexible Staffing Solutions:

  1. Contract Basis: Opt for short-term commitments to meet project-specific needs without the burden of long-term commitments.
  2. Hourly Basis: Gain the flexibility of paying for testing services on an hourly basis, ensuring cost-effectiveness and efficiency.
  3. Weekly Basis: For projects that demand a slightly extended timeframe, our weekly staffing option provides a balanced solution.
  4. Monthly Basis: Enjoy a dedicated testing team on a monthly basis, ideal for ongoing projects and comprehensive testing requirements.

Finding and hiring skilled QA testers can be a daunting task. At Testbytes we understand your challenges and offer a comprehensive solution tailored to your specific needs.

Our Process:

  1. Talent Pool Formation: We leverage diverse sources to create a pool of qualified testers based on your job description. This includes job portals, social media, referrals, and our own database.
  2. Screening and Selection: Our team conducts interviews and assessments and checks references to ensure you receive the best talent. We work with you to define the selection process, ensuring you have the final say.
  3. Hiring and Onboarding: Once suitable candidates are selected, we handle the salary negotiations, offer letters, and onboarding process. You can rest assured knowing everything is taken care of.
  4. Skill Training: We provide continuous training to keep our employees’ skills up-to-date and ensure they meet your evolving requirements. This includes task-specific training, soft skills development, and industry knowledge updates.
  5. Rebadging: Our dedicated team ensures a smooth transition for rebadged employees with proper training, cultural integration, and ongoing support.

Our Services:

  • Onsite Staffing: Testers or teams work directly in your organization, enabling close collaboration and deep integration.
  • Offsite Staffing: Testers work remotely in our environment, utilizing our resources and infrastructure.
  • Hybrid Staffing: A blend of onsite and offsite arrangements, offering flexibility and customized solutions.

Additional Benefits:

  • Fast Recruitment Process: We source, screen, and onboard candidates within 29 days.
  • State-of-the-Art Resources: We offer access to our advanced testing tools and automation frameworks.
  • Multiple Devices: We test your software on a variety of real devices for comprehensive compatibility.
  • Cost-Effective Solutions: Our flexible staffing options help you optimize your budget.

Experience the Difference:

Testbytes is your trusted partner in QA staffing and hiring. We take pride in our commitment to quality, transparency, and customer satisfaction. With our comprehensive services and experienced team, you can focus on your core business while we ensure the success of your software development projects.

Why Quality Assurance is Shifting to Quality Engineering? (Explained)

Table of Contents
1. What is Quality Engineering?
2. What are Quality Assurance and Quality Engineering?
3. The Overall Culture is Changing Along With the Market Expansion
4. The Drawback of the old Working Style
5. Why this Change is Essential
6. How this is Beneficial to the Software Development Community

Software Quality Assurance (SQA) encapsulates the methodologies and tools essential for monitoring and ensuring the quality of software products. Developers carried out manual checks as the final step in the development cycle in the early stages of software development, which was primarily their responsibility.

Yet, as software development complexities burgeon and the market landscape expands, this conventional approach encounters limitations.

However, there is a solution.

What is Quality Engineering?

quality engineering

Quality Engineering (QE) is a systematic and disciplined approach to ensuring the reliability, efficiency, and functionality of software systems throughout the development lifecycle. It involves the application of engineering principles to design, implement, and maintain testing processes and methodologies.

Quality Engineers employ rigorous testing techniques, automation, and continuous integration to identify defects, optimize system performance, and enhance overall software quality.

QE  discipline integrates seamlessly with agile methodologies, emphasizing early defect detection, efficient test automation, and continuous improvement, ultimately delivering robust software solutions that meet or exceed predefined quality standards.

What are Quality Assurance and Quality Engineering? (Differences Explained!)


Quality Assurance (QA) and Quality Engineering (QE) are integral components of the software development lifecycle, each playing distinct roles in ensuring the delivery of high-quality software products. While QA is a broader concept encompassing the entire development process, QE is a specialized discipline within QA focusing on engineering practices for optimal quality outcomes.

Quality Assurance (QA):

QA is a comprehensive approach that involves the entire software development lifecycle. It encompasses processes, methodologies, and activities aimed at preventing defects and ensuring that the final product meets specified requirements. QA is a proactive strategy that involves:

  • Defining Processes: Establishing guidelines, standards, and methodologies for the entire development team.
  • Process Compliance: Ensuring adherence to defined processes throughout the development lifecycle.
  • Audits and Reviews: Conducting audits and reviews to identify deviations from established processes.

Quality Engineering (QE):

QE is a subset of QA that specifically focuses on engineering practices to achieve desired quality outcomes. It involves applying engineering principles to testing and validation processes, emphasizing automation, efficiency, and continuous improvement. Key aspects of QE include:

  • Test Automation: Developing automated test scripts to enhance testing efficiency and coverage.
  • Performance Engineering: Optimizing software performance through load testing and analysis.
  • Continuous Improvement: Iteratively refining processes based on testing outcomes and feedback.

Differences Between QA and QE:

Criteria Quality Assurance (QA) Quality Engineering (QE)
Scope Broader, covering the entire software development lifecycle. Specialized, focusing on engineering practices within QA.
Objective Ensuring adherence to defined processes and standards. Enhancing testing processes, automation, and continuous improvement.
Activities Process definition, compliance monitoring, audits, and reviews. Test automation, performance engineering, and continuous improvement.
Focus Process-centric, ensuring the right processes are followed. Outcome-centric, emphasizing optimal testing practices and efficiency.
Timing Applied throughout the software development lifecycle. Primarily during the testing phase, but influences the entire lifecycle.

The Overall Culture is Changing Along With the Market Expansion

As the overall culture undergoes a transformative shift and markets expand, the adoption of Quality Engineering (QE) emerges as the best option for ensuring the success and sustainability of software solutions. Several factors contribute to the compelling rationale behind choosing QE as a cornerstone in this evolving landscape:

  1. Agile Compatibility:
    • QE seamlessly integrates with Agile methodologies, aligning with the dynamic and iterative nature of modern software development. It enables continuous testing and quality checks throughout the development lifecycle, fostering quicker releases and responsiveness to changing market demands.
  2. Enhanced Time-to-Market:
    • The fast-paced market expansion demands accelerated development cycles. QE, with its emphasis on test automation and efficient testing practices, significantly reduces time-to-market. This agility is crucial for staying ahead of competitors and swiftly adapting to evolving customer needs.
  3. Cost Efficiency:
    • Traditional methods of software testing can be resource-intensive and costly. QE optimizes resources through test automation, allowing repetitive tests to be executed efficiently. This not only reduces testing costs but also enhances the overall cost efficiency of the software development process.
  4. Improved Customer Experience:
    • QE ensures that software products meet or exceed customer expectations by identifying and rectifying defects early in the development process. This results in more reliable and user-friendly products, enhancing the overall customer experience and satisfaction.
  5. Continuous Improvement:
    • The culture shift towards continuous improvement aligns with QE principles. Through continuous testing, feedback loops, and data-driven insights, QE facilitates an environment of ongoing enhancement. This adaptability is vital in an environment where market dynamics and user preferences are in constant flux.
  6. Risk Mitigation:
    • In an expanding market, the risks associated with software defects and failures are amplified. QE, with its comprehensive testing practices, mitigates these risks by identifying potential issues early in the development cycle. This proactive approach protects the brand reputation and ensures a smoother market entry.
  7. Scalability and Flexibility:
    • QE strategies are designed to scale seamlessly, accommodating the increased complexity and demands of an expanding market. The flexibility of QE allows teams to adjust testing approaches based on the specific requirements of diverse projects and market segments.

The Drawback Of The Old Water-fall Model      

1. Lack of flexibility: The waterfall model is a rigid and linear approach to software development, which means that it is not well-suited for projects with changing or uncertain requirements. Once a phase is completed, it is difficult to go back and make changes. This can lead to problems if the requirements change or if there are bugs that were not caught in the earlier phases.

2. No working software is produced until late during the life cycle: In the waterfall model, software is not tested until the end of the development cycle. This means that there is no way to get feedback from users or to identify and fix bugs early on. This can lead to delays in the project and to software that is not what the users want or need.

3. High amounts of risk and uncertainty: The waterfall model is a risky approach to software development because there is no way to mitigate the risks of requirements changes, bugs, or other problems until late in the project. This can lead to costly delays and rework.

4. Limited user involvement: In the waterfall model, users are not involved in the development process until the testing phase. This means that their feedback is not taken into account until it is too late to make changes. This can lead to software that does not meet the needs of the users.

5. Poor communication and collaboration: The waterfall model can lead to poor communication and collaboration between different teams involved in the development process. This is because there is no opportunity for teams to share information and work together to solve problems.

6. Does not accommodate iterative development: The waterfall model is not well-suited for iterative development, where software is released in small increments and then improved based on user feedback. This is because the waterfall model requires that all requirements be known upfront, which is not possible with iterative development.

7. Does not capture emerging requirements: The waterfall model does not allow for the capturing of emerging requirements, which are requirements that are not known upfront but that become known as the project progresses. This can lead to problems if the requirements change significantly after the initial requirements have been defined.

8. Can lead to scope creep: Scope creep is when the scope of a project increases beyond what was originally agreed upon. This can happen in the waterfall model because there is no opportunity to get feedback from users or to identify and fix bugs early on. As a result, changes may need to be made late in the project, which can increase the cost and schedule of the project.

All these bottlenecks have resulted in the redefining of the role of quality analysis and culminated in the birth of quality engineering.

Why this Change is Essential

The imperative shift from Quality Assurance (QA) to Quality Engineering (QE) is propelled by the evolution of services rooted in architectural models. The paradigm shift sees teams independently defining their business implementations as a network of connected but independently governed services constrained by strict contractual protocols. This transformation necessitates a fundamental change in the approach to testing for QA engineers.

In this new landscape, QA engineers grapple with writing code even before its existence, engaging post-design to identify core functionalities for required tests. The adoption of frameworks mimicking dependencies allows teams to work seamlessly without waiting for upstream and downstream dependencies, expediting the development process.

How this is Beneficial to the Software Development

This transformative approach has reshaped the role of software developers, empowering them to not only build infrastructure but also take charge of identifying test scopes, mitigating risks, and defining quality criteria across the entire spectrum, from individual units to the final acceptance of testing and planning. This modern role is now coined as a “Software Developer in Test” (SDET).

The increased recognition and pay that these professionals now receive underscores the shift toward SDETs in addition to the evolution of duties. SDETs are being remunerated at levels commensurate with traditional developers, acknowledging the critical nature of their contributions.

Moreover, companies increasingly recognize the invaluable role of Quality Engineers in the software development process. Their impact is not merely seen as a cost but as an investment in delivering high-quality, reliable software. This paradigm shift not only elevates the status of Quality Engineers but also signifies a strategic move by companies to prioritize quality assurance as an integral part of the development lifecycle.

By integrating Quality Engineers seamlessly into the development process, organizations benefit from enhanced collaboration, faster release cycles, and a proactive approach to quality. SDETs contribute not only to testing but also to the overall improvement of development practices, ensuring that quality is not an afterthought but an inherent aspect of the software creation process. The resulting synergy between developers and Quality Engineers not only fosters a culture of quality but also propels software development towards higher efficiency and customer satisfaction.


As we navigate the ever-evolving landscape of software development, the role of quality engineering has transformed from mere assurance to a cornerstone of the development process. The construction of robust test-key infrastructure is paramount, enabling effortless data capture, comprehensive analysis, and actionable insights that guide effective mitigation strategies.

Quality engineering is rapidly emerging as a specialized field, demanding a unique blend of expertise that seamlessly integrates with data science.

This convergence empowers quality engineers to harness the power of data, driving informed decisions and propelling software development toward unprecedented levels of excellence.

What is Compliance Testing? How to do it?

Compliance testing evaluates and assesses whether your software fulfills all the regulations, standards, requirements of specifications, etc. that it has to stand true on.

The process can be considered more as an auditing task to ensure that it fulfills required standards.

It is many times also referred to as conformance testing.

Attributes of compliance testing

  • Robustness
  • Performance
  • Interoperability
  • Functions
  • Behavior of system

What are the prerequisites of compliance testing?

  • The product development should be complete with all the features working as expected.
  • The documentation and user manuals for the product should be available to help understand and recheck for compliance.
  • The online support and documentation, if applicable should be the latest version.
  • Functional and integration testing should be complete and should satisfy the exit criteria.
  • Escalation matrix should be available along with the point of contact for development, testing, and management teams
  • All licenses should be up to date.

Importance of Compliance Testing

Here are a few points that will help you understand its utility.

  • To validate if your software fulfills all the system requirements and standards.
  • To assess if all the related documentation is complete and correct.
  • To validate the software design, development, and evaluation are carried out as per specifications, standards, norms, and guidelines.
  • To validate if system maintenance is determined as per specified standards and recommended approach.
  • To assure that your software is free from any sort of complaints from regulatory bodies, regulatory compliance testing is performed.

Who executes Compliance testing?

Many companies do not consider it mandatory. Why? executing the test largely depends on the management.

However, If they consider a need to execute compliance testing, they hire or ask the in-house team to conduct compliance testing.

Many organizations also deploy a panel of experts or a regulatory body to assess and validate various regulations, specifications, policies, and guidelines.

Vulerability assessment protection

What to test in Compliance testing?

The process is initiated by the management taking care of the complete understanding of the team about various regulations, specifications, guidelines, etc.

To ensure the best results and quality assurance, all the regulations and standards should be clearly mentioned to the team to avoid any ambiguities.

  • Requirement objectives
  • Scope of requirements
  • Standards that rule the implementation
  • Call of the software to be developed

What are the examples of compliance testing?

Some of the examples of compliance testing are:

  • User Access Rights and Security Regulations
  • Program change and control procedures
  • The procedure and guidelines for documentation
  • The guidelines for program documentation
  • Logs review
  • Audit of the software artifacts including licenses

What is not tested in compliance testing?

Some teams consider system and integration testing to be part of compliance testing as well. But that is not true.

Compliance does not mean re-running the system or functional tests.

On the contrary, compliance tests are a set of specifically designed tests that are carried out at the end of the software development cycle before rolling out the software product to production.

When to perform Compliance Testing?

There are some countries where compliance testing is mandatory and they have specific guidelines as well to accomplish this testing.

In most other countries, it is purely a management call. If the management wants to strictly follow the set guidelines, rules, and best practices, it will be pushing for a compliance test.

For the compliance tests to be carried out, the first step would be to chart out a detailed document with the procedures, standards, and methodology. It will be based on these that the compliance tests are designed.

Also, the compliance test would differ from one domain to another. Thus these tests need to be designed as per the industry and domain needs.

How to perform compliance testing?

it is more like an audit and follows no specific testing methodology.

You can simply carry it out like other general testing methods.

Here is an overview of the generic compliance testing methodology that may help you in performing it.

  • The first step is to collect precise details about all specified standards, norms, regulations, and other relevant criteria.
  • In the next step, you are required to document all the norms and standards clearly and precisely.
  • In the third step, you will have to keenly assess all the development phases against the documented standards and norms to identify and detect any deviations or flaws in the implemented process.
  • The next step includes creating a report and reporting all the flaws to the concerned team.
  • Lastly, you are required to re-verify and validate the affected areas post-fixation to ensure conformance to the required standards.
  • If required certification is provided to the system for the compliance of required norms and standards.

What is the need for compliance testing?

Here are the reasons

  • Safety: The safety of the customers and the safety of the product are the primary reasons for conducting compliance tests. Compliance tests are designed to find negligence issues and to ensure all safety standards are met.
  • Quality: Improved and proven quality is another reason why we should push for compliance testing for the products. Apart from the compliance test, it is also important to conduct periodic audits.
  • Legal Requirements: In some cases, the companies are legally bound to conduct compliance tests before releasing the products. If these tests are not performed legal action can be taken against the company and their license can also be canceled.
  • Customer Satisfaction: Customers would have more confidence in a product that is tested and is marked compliant. It is thus good for the company and its reputation as well.
  • Conformance: Compliance with the physical standards ensures conformance and compatibility with other products in the market that might be from different manufacturers.

Who sets the standards for compliance testing?

Most commonly, there are external organizations that come with the standards in compliance testing for various industries and are then accepted by a majority of the industries.

Some organizations are

Based upon the required standards and your system type there are many compliance testing tools that are available in the market.
Here are the names of a few commonly used compliance testing tools.

  • EtherCAT conformance testing tool
  • MAP2.1 conformance testing tool
  • Software Licence Agreement OMS Conformance Tester 4.0
  • CANopen Conformance test tool

Advantages of Compliance Testing

Unfortunately, compliance testing has not yet become a widely accepted part of STLC, but it is advisable to carry around to assure better performance and compliance of your software.

Listed below are a few points that might help you to better understand the advantages of carrying out the process

  1. It assures proper implementation of required specifications
  2. It validates portability and interoperability
  3. It validates whether the required standards and norms are properly adhered to
  4. Validate that the interfaces and functions are working as expected
  5. Can help you identify the areas that are to be confirmed with those which are not to be confirmed such as syntax and semantics

Disadvantages of Compliance Testing

Here are some challenges that you might incur while doing compliance testing

  1. To get the best results, you need to identify the class of the system, and then the testing has to be carried out based on the class following a suitable methodology
  2. You will have to specific specifications into Profiles, Levels, and Modules
  3. You will need to have the complete know-how of different standards, norms, and regulations of the system to be tested.

What is the need for compliance testing?

One may wonder why they need compliance testing when functional, system, and integration testing are already done.
Here are the reasons, why we need compliance testing.

  • Safety: The safety of the customers and the safety of the product are the primary reasons for conducting compliance tests. Compliance tests are designed to find negligence issues and to ensure all safety standards are met.
  • Quality: Improved and proven quality is another reason why we should push for compliance testing for the products. Apart from the compliance test, it is also important to conduct periodic audits.
  • Legal Requirements: In some cases, the companies are legally bound to conduct compliance tests before releasing the products. If these tests are not performed legal action can be taken against the company and their license can also be canceled.
  • Customer Satisfaction: Customers would have more confidence in a product that is tested and is marked compliant. It is thus good for the company and its reputation as well.
  • Conformance: Compliance with the physical standards ensures that conformance and compatibility with other products in the market that might be from different manufacturers.

Types of compliance testing?

  1. Mandatory Testing: In some countries for security-related software products, compliance testing is legally mandatory. This testing is either performed by a govt agency or a third party appointed by the govt. For the product to be released it requires certifications from the govt. Failing to comply with tests could mean withdrawing the product from the market, fines, payment of damages, or more.
  2. Obligatory Testing: When 2 companies are working with each other, one company may ask for a compliance test report from the other. Failure to perform the tests could lead to contract termination and subsequent loss of business.
  3. Voluntary Testing: To ensure that the process is carried out in an unbiased manner, companies may engage third parties to do compliance testing. The company may not be legally bound to do the test but want to perform the tests to ensure the best product rollout.
  4. Internal Testing: Companies can also engage the teams internally to perform compliance tests to improve the performance of their products and services. This is not a regulation but is done based on the directive from the management.

Standards in compliance testing

  1. SO 9001 (Quality Management System)
  2. ISO/IEC 27001 (Information Security Management)
  3. ISO 13485 (Medical Devices)
  4. HIPAA (Health Insurance Portability and Accountability Act)
  5. PCI DSS (Payment Card Industry Data Security Standard)
  6. GDPR (General Data Protection Regulation)
  7. Sarbanes-Oxley Act (SOX)
  8. COBIT (Control Objectives for Information and Related Technologies)
  9. IEEE 829 (Software Test Documentation)
  10. OWASP Top Ten (Web Application Security)

Forms of compliance testing

 Internal Testing

This is performed internally by the organization to ensure that the software and processes adhere to the policies, standards, and best practices of the business. It contributes to the quality and consistency of software development.

External or legally required testing for compliance:

Compliance testing of this nature is mandated by law by governmental authorities or industry-specific regulatory organizations. It guarantees compliance of the software with obligatory regulations, laws, and standards. There may be legal repercussions for noncompliance.

Testing for mandatory or obligatory compliance:

Comparable to testing that is mandated by law, this is necessary to comply with particular industry standards and regulations. Instances of such adherence encompass healthcare software conformity with the Health Insurance Portability and Accountability Act (HIPAA) and payment processing applications’ adherence to the Payment Card Industry Data Security Standard (PCI DSS).

Testing for Voluntary Compliance:

Organizations may elect to undergo voluntary compliance testing as a means of showcasing to clients or business partners their dedication to quality and safety. Compliance with industry-recognized standards, even in the absence of legal requirements, may be required.

Compliance testing in various forms is of the utmost importance in guaranteeing that software satisfies the mandatory criteria, be they those mandated by legislation, industry standards, or internal quality assurance processes. They aid in ensuring that software is dependable, secure, and conforms to stakeholders’ expectations.


Delivering glitch-free software enhances your customer’s trust in you. Compliance testing is another step that assures that your system is free from any flaws and glitches…

Strategies for Testing in AI Applications Best Practices and Key Considerations

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.

Mobile app test cost calculator

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

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.

benefits of AI software testing

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:

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.

benefits of leveraging AI Software testing

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?

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.

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.).

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.

Testing AI Application

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.

App Bug fixing


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.

Software Testing Latest Trends & Technology in 2023

Software testing is the most significant part of the Software Development Lifecycle 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.

In this research blog, we discuss recent trending software testing topics that are being researched industriously around the world. The software industry goes through a lot of research and modified methodologies that keep the software quality top-notch for the end-user.

Read Also: Popular Websites to Find Software Testing Research Papers Free & Paid

We provide introductory information about the latest trending topic the exponential and unprecedented change in technology affects the way in which organizations develop, validate, deliver, and operate software. Hence, users must consistently innovate and restore themselves by finding the solution to optimize practices and research trends to develop and deliver high-quality software quickly. Along with these trends, there are testing solutions which have the potential to address the challenges in software testing.

Pen testing cost + app testing strategies

Latest Technology Trends in Software Testing

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

1. QAOps

QAOps is an emerging practice that integrates QA (Quality Assurance) into the software delivery pipelines. It necessitates the QA team to work directly with the operations team and the development team. We can attain this by integrating QA procedures, automation, and a QA reporting dashboard with the software development cycle as shown in following figure.


  • Working with multiple teams allows you to learn and experience how different teams work. It also allows you to improve your skill level in a variety of areas. QAOps entail testing the product or a specific component of the product as soon as the update is incorporated, so the QA team does not have to wait for a new build. This assists the QA team in identifying problems early, and correcting these problems sooner rather than later can prevent further problems from occurring as a result of these defects.
  • Customers will have a better experience using your product since QAOps incorporates continuous testing. Your consumers will be far more happy with a better degree of quality and dependability than they would have been otherwise.
  • Because testing occurs on a continual basis, QAOps keeps the testing team interested. It saves the QA team from having to wait until the application is ready for another round of testing. Furthermore, because the QA staff is neither idle or bored, their morale should improve.
  • The QAOps framework improves communication between QA engineers and developers. Software developers, operational people, and everyone else engaged in the CI/CD process must collaborate closely with QA engineers.
  • QAOps support the fastest software development cycle and keep the testing team continuously engaged. The QAOps are of high quality and dependability. The QAOps reduce the execution time by adapting automation.

You can search research article related to the QAOps is available on following link


Read Also: Personality Analysis of Software Testers A Scientific Approach
2. Scriptless automation testing
  • It is a method of automating tests without developers writing coded scripts. The tools are often built on test automation frameworks such as Selenium which is a free (open-source) automated testing framework used to validate web applications across different browsers and platforms.
  • A scriptless testing tool can record a tester’s activities as it navigates through features on application screens. The tool will produce the identical test steps that you would normally write a test script for by capturing these actions. As a result, scriptless testing is restricted to interacting with UI components.  Automated UI testing is quickly becoming the new norm. This comprehensive guide dives into UI automation, one of the hottest trends in the world of Software testing. It is designed to provide you with knowledge across the broader UI test automation spectrum, including what it means, how to perform it, and the various challenges it presents. Scriptless testing is constrained by the same constraints as the test framework it employs. As a result, it may not test things like captcha, barcodes, and so on.


  • Though the term implies script-free testing, certain solutions do allow for the addition of scripts for complicated test cases.
  • Scriptless test automation enables the testers and business users to automate test cases without worrying about the coding. It helps to achieve faster results and reduces the time expended to understand the code.

Characteristics of script-less testing: 

  • Traditionally, automated testing necessitates extensive script creation, which frequently necessitates strong engineering skill sets.
  • These test scripts are easily broken as the app changes or as the app runs on multiple devices.
  • This is why scriptless automation tools are appealing.
  • They provide enterprises with a low-complexity and cost-effective way to leverage the benefits of Automated Testing without the complexity or cost of script creation.

As a result, it is critical to guarantee the following when selecting a mobile Scriptless Automation platform:

I. Test scripts may be developed in a simple “no-code” fashion.
II. The test scripts can run on a wide range of devices and operating systems without failing.
III. To avoid vendor lock-in, test scripts might be exported in an open standard e.g., Appium which is an open-source framework that allows QAs to conduct automated app testing on different platforms like Android, iOS, and Windows.

Source of research article connected to Scriptless automation testing is available on


3. Big data testing:
  • Big Data Testing can be defined as the procedure that involves examining and validating the functionality of the Big Data Applications.
  • In Big Data Testing a method that involves inspecting and testing the functionality of big data applications. “Big Data” is a massive accumulation of data that typical storage techniques cannot handle.
  • To ensure that all of its capabilities perform as planned. Big data testing ensures that the big data system functions smoothly and without errors while preserving performance and security.
  • The never-ending surge for the Creation, Storage, Retrieval and Analysis of the colossal volumes of data, triggered the motivation behind the origin of Big Data Testing.


Strategy for Big Data Testing:

  • Big Data application testing is more concerned with data processing than with particular elements of the software product. The cornerstones of Big data testing include performance and functional testing.
  • QA engineers in Big Data testing approach validate the successful processing of terabytes of data utilising commodity cluster and other supporting components. Because the processing is so quick, it necessitates a high level of testing expertise. Batch, real-time, and interactive processing are all options.
  • In addition, data quality is a significant consideration in Hadoop testing. Before testing the application, it is vital to examine the data quality, which should be included in database testing.

Source of research article connected to Big data testing is available on


Read Also: History of Software Testing Estimation Models for Cost Analysis
4. IoT testing
  • IoT testing includes functional and integration testing relevant to the specifics of distributed architectures, performance testing to check how the app handles large volumes of streaming data, security testing at the application, gateway, and IoT device levels. Because every IoT device sends and receives data over the Internet, it is critical that your IoT devices can communicate sensitive information wirelessly before coming to market.
  • As a result, many IoT companies rely on IoT automation, penetration, and performance testing solutions to uncover flaws before they reach users.
  • IoT testing ensures that IoT devices meet stated standards and perform as intended.

IoT testing

The difficulties encountered during IoT testing:

  • Both the network and internal communication must be examined.
  • Because the tasks are performed via the Internet, security and privacy are major problems in IoT testing.
  • The complexity of the software, as well as the system itself, may mask vulnerabilities or problems discovered in IoT technology.
  • Memory, processing power, bandwidth, battery life, and other factors are all limited.

Suggestions for efficient IoT testing:

  • Gray box testing and IoT testing should be conducted concurrently to allow for the creation of effective test cases. This assists us in comprehending the operating system, architecture, third-party hardware, new connections, and hardware constraints.
  • Scalability, adaptability, connection, and security are all critical for IoT and require real-time operating systems.
  • IoT testing may be automated to make it more effective.

Source of research article connected to IoT testing is available on


5. AI & ML based Software Testing
  • AI and ML help organizations eliminate testing gaps by augmenting people’s skills and capacities to analyze real-time data.
  • The Al and Ml testing frameworks can easily identify problems, and with frequent changes to the algorithms, it is possible to find even minor errors. Artificial Intelligence (AI) and Machine Learning (ML) technology are well-trained to analyse data, recognise schemes and patterns, and perform and assess tests without the assistance of humans.
  • Deep learning and artificial neural networks enable this when a computer self-educates based on specified data sets or data taken from an external source such as the web.
  • The goal of AI is to replicate human intelligence in robots and is to develop a technique for solving issues that enables software to oversee operations without the need for manual programming.

AI ML Testing

  • The latest AI and ML technologies in the digital era require a new approach to software testing while handling complex systems and functionalities. Testing AI platforms enables companies to ensure adequate security measures for their complex applications.
  • Advances in software and AI world have paved the way for Robotic Process Automation (RPA). It is the most recent technology which has the capability to re-invent the business process management landscape.
  • However, a kind of artificial intelligence known as machine learning helps robots access information and carry out diverse activities. The ML technology helps AI systems understand learning processes and derive insights.
  • Software testing uses up company resources and doesn’t improve the functioning of the programme, according to research. A new regression cycle starts when regression testing reveals a new error introduced by a revision code. Engineers are frequently required to design testing scripts for software applications, and their expertise must be on par with that of the original app’s creators.
  • Machine Learning Changing Software Testing – Software applications are constantly changing as users want additional features or business processes to be updated; however, these changes often cause automated tests to no longer work correctly.

Source of research article connected to AI & ML based Software Testing is available on https://www.mendeley.com/search/?query=AI+%26+ML+based+Software+Testing&dgcid=md_homepage

6. Shift left Software Testing
  • Software developers are being incorporated into the testing cycle earlier than ever before, movement in the testing world is commonly known as shifting left.
  • The “shift left” testing trend aims to move testing closer to the beginning of the software development process. A project can decrease the amount of problems and improve the quality of the code by testing often and early. The objective is to avoid discovering any significant defects that need for code patching during the deployment process.
  • Moving the testing phase earlier in the software development life cycle is what the shift left movement is all about. Approaches where testing is only done at the very end of the software development life cycle should be avoided. We implement testing in the early phases of software development using shifting left.

Shift Left testing

  • Shift Left is a practice intended to find and prevent defects early in the software delivery process. The idea is to improve quality by moving tasks to the left as early in the lifecycle as possible. Shift Left testing means testing earlier in the software development process.
  • A Shift Left testing approach may not always be able to deliver optimal performance and functioning in a real-world environment.

Source of research article connected to Shift left Software Testing is available on https://search.springernature.com/search?q=Shift+left+Software+Testing

7. DevOps

DevOps – is a combination of Development & Operations  it is a Software Development methodology that looks to integrate all the Software Development functions from development to operations within the same cycle. It is a modern code deployment approach that significantly helps in the collaboration and coordination among various teams and accelerates the software delivery process with faster releases.

DevOps Cycle


DevOps Cycle

Following figure shows the impact of DevOps on software testing

Impact of DevOps

8. Accessibility Testing

Accessibility testing is another type of software testing used to test the application from the physically challenged person’s point of view. Accessibility testing is the practice of making your web and mobile apps usable to as many people as possible.


This sort of software testing not only focuses on verifying app usability, but it also makes sure that the application can be used by people with many disabilities, including visual, auditory, physical, speech, cognitive, language, learning, and neurological disabilities.

Read Also: Improving Software Test Automation Using Different Algorithms
9. Regression Testing

Regression testing is a software testing practice that ensures an application still functions as expected after any code changes, updates, or improvements. Regression testing is responsible for the overall stability and functionality of the existing features.

Regression Testing

Regression testing can be performed using the following techniques:

1. Re-test All: Re-Test is one of the approaches to do regression testing. In this approach, all the test case suits should be re-executed. Here we can define re-test as when a test fails, and we determine the cause of the failure is a software fault.

2. Regression test Selection: In this technique, a selected test-case suit will execute rather than an entire test-case suit.

  • The selected test case suits divided in two cases

    A. Reusable Test cases: Reusable test cases can use in succeeding                regression cycle.
    B. Obsolete Test cases: Obsolete test cases can’t use in                                     succeeding  regression cycle.

3. Prioritization of test cases:

Prioritize the test case depending on business impact, critical and frequently functionality used. Selection of test cases will reduce the regression test suite.

10. Performance Testing

Performance Testing is a type of software testing that ensures software applications to perform properly under their expected workload. It is a testing technique carried out to determine system performance in terms of sensitivity, reactivity and stability under a particular workload.

Performance Testing

Today’s businesses become successful only if their business-critical mobile and web applications perform well under varying loads and should essentially deliver great performance.

11. User Testing

User testing is the process through which the interface and functions of a website, app, product, or service are tested by real users who perform specific tasks in realistic conditions. The purpose of this process is to evaluate the usability of that website or app and to decide whether the product is ready to be launched for real users.


In this method, the real users test the apps by considering various real-time use cases and the feedback from these users helps in improving the application for the end-users.


Software testing is a process of evaluation that either the specific system meets its originally specified requirements or not and the rise in the number of applications used by different organizations has increased the demand for software testing. This blog highlights the most trending software testing topics in research and aims to discuss the existing as well as improved software testing topics and popular platforms for the better quality assurance purposes.

The primary goal of this blog is to provide a basic introduction to trending topics as well as the research sources used for references and to help aspiring researchers in their search for researchers.

Thus, there is a strong need to adapt the latest testing trends for all the software industries in the world, which will help them to adapt to the requirements of the modern world. In face of newer and higher demand of software testing, it is necessary to constantly summarize new achievements, study fresh hotspots and propose different ideas in order to promote the study on software testing system engineering, to facilitate the rapid development on software testing field and industry.

How Many Roles Can a Software Tester Play

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.

Read Also: What is the Optimum Software Developer to Software Tester Ratio?

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 Role Play

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

Read Also: What’s The Role of a Computer Game Tester?

  • 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.

Read Also: 50 Automation Testing Questions for Interview Preparation


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

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.

App Bug fixing

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.

Read Also: Agile Software Development Methodologies

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.

Read Also: What is Agile Testing? Process, Methodology and Strategies

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:


  • 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

  • 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.

Read Also: Agile VS DevOps: Difference between Agile and DevOps

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.


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.

What is the Optimum Software Developer to Software Tester Ratio?

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.

Read Also: Difference Between Software Tester VS Developer

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.

Read Also: Quality Assurance (QA) vs Quality Control (QC)

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.


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.

Read Also: Salary of Developer vs Tester : Who Earns More?

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.


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.

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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.