Tag: test data

5 Test Data Generation Techniques You Need to Know

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It is quite well-known that testing is the process in which the functionality of a software program is tested on the basis of data availability. The data available for conducting any test is the medium using which the entire functioning of the software is tested and then, the necessary changes can be implemented. But, what exactly is test data?
app testing
In simple terms, test data is the documented form which is to be used to check the functioning of a software program. It is the collection of data that affects or is affected due to the implementation of a specific module. Test data can be categorized into two categories that include positive and negative test data. Positive test data is used to validate whether a specific input for a given function leads to an expected result. Negative testing is done to check a program’s ability to handle unusual and unexpected inputs.
Test data generation is another essential part of software testing. It is a process in which a set of data is created to test the competence of new and revised software applications. This can either be the actual data that has been taken from the previous operations or a set of artificial data designed specifically for this purpose.
Generally, test data is generated in sync with the test case for which it is intended to be used. There are multiple ways in which test data can be generated. Some of these are as mentioned below:

  1. Manual Test Data Generation

This is a simple and direct way of generating test data. Often done to cover all the essential test cases, the test data generated is, then, used to test various scenarios. Some of the common types of test data include null, valid, invalid, valid, data set for performance and standard production data.
One of the most prominent benefits of using this technique for test data creation is that it does not require any additional resources to be factored in. The test data is generally created by the testers using their own skills and judgments. However, this technique has its own disadvantages. The technique is time-taking and thus, leads to low productivity. It is difficult to get more data added as doing so will require a number of resources. Along with this, it is also important for the person entering the data to have a domain knowledge to create data without any flaw.

  1. Automated Test Data Generation

 This technique makes use of data generation tools, which, in turn, helps accelerate the process and lead to better results and higher volume of data. One of the common tools that is used in this technique is Selenium/Lean FT and Web services APIs.
One of the major benefits of automated test data creation is the high level of accuracy. There is also a better speed and delivery of output with this technique. The best aspect of this technique is that it can perform without the presence of any human interaction and during non-working hours. This, in turn, helps in saving a lot of time as well as generating a large volume of accurate data.
The major disadvantage of using this technique is its high cost. Moreover, these are available in a specific framework, which, in turn, makes it difficult to completely understand the system. This, in turn, makes it a mandate for the human resources to possess requisite skills as well as for the companies to provide adequate training to its available resources.

  1. Back-end Data Injection

Back-end data injection technique makes use of back-end servers available with a huge database. This is because the existing databases can be updated directly using the test data stored in the database, which, in turn, makes a huge volume of data quickly available through SQL queries. However, this test data generation technique eliminates the need of front-end data entry, it should be ensured that this is done with utmost attention and carefulness so as to avoid any sort of fiddling with database relationships.

The best aspect of using this technique is in terms of its ability to quickly inject data into the system. It also demands less technical expertise from the person executing this process. Above all, it allows one to create backdated entries, which is one of the major hurdles while using manual as well as automated test data generation techniques.
But, this technique has its own drawbacks and can lead to disaster if not implemented correctly. It also requires one to have domain expertise so that he/she is able to understand the data flow in the system as well the entry of accurate database tables. There are also high risks of corrupted databases as well as application due to this technique. Therefore, it becomes important for the team to have a proper database backup while using this technique.

  1. Third-Party Tools

Easily available in the market, third party tools are a great way to create data and inject it into the system. These tools have a complete understanding about the back-end applications data, which enable these tools to pump in data similar to the real-time scenario. Thus, it makes diverse data available in high volume for the testers.
The major benefit of using third-party tools is the accuracy of data that this offer. This is owing to the tools’ thorough understanding of the system as well as the domain. Another advantage is in terms of taking care of the backdated data fill, which allows users to execute all the required tests on historical data. Moreover, performing these tests does not require one to have detailed domain knowledge and expertise.
What bothers the users of third party tools is their huge cost that can burn a hole in the organization’s pocket. Another dis-advantage, is their limited use only to a specific type of system, which, in turn, limits their usage for the users and applications they can work with.

  1. Path wise Test Data Generators

 Considered to be one of the best technique to generate test data, this technique provides the user with a specific approach instead of multiple paths to avoid confusion. Using this technique helps the users to gain specific and better knowledge as well as predict its coverage. This technique makes the user enter the program to be tested, as well as the criteria on which it is to be tested such as path coverage, statement coverage, etc.
The test data generation techniques are multiple and varied. All one needs to do is choose the best one as per their requirements and program. If done properly, this can benefit the company in different aspects and lead to remarkable results.

What is the Need For Test Data Generation Techniques

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In order to ensure the quality of the software before launch, a team of professional quality-testers performs various kinds of software testing techniques. Test data generation techniques make use of a set of data which can be static or transnational that either affect or gets affected by the execution of the specific module.
The data can be used for positive and negative testing to confirm whether the desired function is producing the expected results or not and how software application will handle unexpected or unusual data?
Prevention Is Better Than Cure
Typically test data generation techniques are used in conjunction with test cases and test data that can be obtained manually, by automated test data generation tools, or through a copy of test data from production to testing environment,  from legacy client’s system.
The main purpose or the need for test data generation can be summarized as follows:-
1) Need of Test data generation techniques for performance testing: –
The test data which require for testing that how fast software will respond or perform under workload must be real or live data which can be obtained through customers. Their feedback or an existing set of data can give you insight into how real-world data might look like.
If you are working in a team of maintenance testing project, you can copy test data from the production environment, but while copying, it will be beneficial to anonymize – customers Bank Details, Social Security Number, and Credit Card Numbers etc.
2) Need of Test data generation techniques for security testing:
The test data which require for testing security feature of the software which it can offer to the customer’s crucial private information must fulfill criteria like integrity, authentication, and authorization.
For Integrity (check information provided by the system is correct or not) category, test data can be designed on the basis of databases, code, file structures, and design. By various permutations and combinations of user-names and passwords test data Authentication (checks the identity of the user) criteria can be tested.
The various combinations of roles, users, and operations test data will check Authorization (it checks the rights or privileges to perform certain operations by specific users) factor.
3) The need of Test data generation techniques for functional testing: –
The test data for functional testing must include positive and negative scenarios, boundary conditions (test data values at the extremities of all possible values), and all functional flows defined in the requirement.
A single set of data can be used for testing similar test cases. To keep the test data pool optimized test data such as client ID’s, country codes can be reused across test cases.
Test data creation utility or tool which is capable of generating a spectrum of data to satisfy all the data requirements so that data can be reused across the release of the product will be beneficial for functional testing.
4) Need of Test data generation techniques for Black Box testing:-
In such testing, codes are invisible to the tester and he/she can use techniques like No data, Boundary Condition Data Set, Illegal Data Format, Valid/Invalid Data, Decision Table Data Set, State Transition Data Set, Use Case Test Data etc.
Test data generation is an important area of research to carry out proper software testing approach with reduced cost as the final aim of this method is to satisfy functional, non-functional or business requirements.

A well-defined test data can certainly help you identify and correct the flaws throughout the testing mechanism. Even after making the right choice of test data technique make sure that it is re-evaluated in every phase of the software testing life cycle.