An Expert Guide On Test Data Generation: An Answer To The What, How And Why’s Of It

1. An Expert Guide On Test Data Generation: An Answer To The What, How And Why’s Of It

2. We all know that for a seamlessly functioning application and to efficiently deal with the edge cases, it is vital to test generated data for all cases. • However, the process of testing the processes requires hundreds of thousands of data cases. This generated data passes from initial conditions to the final output and thus helps in defining the success of the software. Any fallback during the stages of testing is an indication of bug/error existence. • One may think test data management is trivial but wait, Do you know how much challenging it is? This blog plans to introduce the Test Data to the unknowns and elaborate more on the quick tips to produce test data. So, keep scrolling… • First and the foremost thing to start with is, knowing what test data is? So, when a software analysis is done, it needs input to get tested. This input is known as Test Data. These data are tested against specific modules and gives an output/feedback that can verify the functionality expectation. When the expected results are achieved, it is called positive testing.

3. Same way, when these data are tested against unusual, extreme or exceptional test cases, it is called negative testing. And hence, if the data is poorly made, you may not be able to test the software thoroughly, and this may hamper the quality of the software. • Then the question which pops up next is, how are you going to generate test data? It is important for you to generate relevant test data that is suitable for the test cases that you have planned to test. These test data can be generated in four different ways namely; • Manually; • Mass copy of data from production to testing environment; • Mass copy of test data from legacy client systems; • Automated Test Data Generation Tools. • One should plan the test data in advance before the test execution; otherwise, the scenario gets time-consuming. In the next segment, we will discuss some various testing types and their requirements for testing data.

4. Test Data for White Box testing: For white-box testing, test data is collected directly from the code to be tested. Moreover, for collecting the test data following things should be taken into consideration. • You need to cover maximum branches of the software testing cases as possible. Just make sure that the test data generated are tested at least once. • Perform Path testing: ensure all the paths are covered in the testing and maximum cases are covered. • Perform Negative API testing: Some invalid and exceptional parameters need to be included for testing different methods. You can also include an invalid combination of arguments to check the validity of the methods.

5. Test Data for Performance testing: • Performance testing deals with the system and its performance under the workload scenario. The motive behind performing this is to find the bottlenecks of the software. But only the data that resemble real data used in the production needs to be checked. So, how do you get this data? The obvious answer is, from the user, “Customers”. • This real data can be obtained from them in the form of feedback, or they might provide you with the existing set of data that can be tested against cases. If you are at a stage of maintenance testing, take the data from the production environment and put it into the testing bed. Make sure that you do not include sensitive customer information for checking the test cases.

6. Test data for Security testing: This testing type ensures that the data is protected from malicious intent whenever an input data is provided. The test data intended for software security should include and abide by the following cases. • Confidentiality: Sensitive data should not be shared outside the parties, and one should maintain the confidentiality of the same. • Integrity: Check whether the data provided by the system is authentic and correct. For designing the same, you can thoroughly look at the design, code, file structures, and more.

7. Authentication: Test data can be used to set up an identity of the user. Such test data can be designed using multiple combinations of usernames and passwords and also check that the access is limited to authorized people only. • Authorization: All the users should know their rights, and this test data tells the privileges of people to perform certain operations. Test data for Black Box testing: In Black box testing, the tester doesn’t know which code is inserted for testing. These test cases should meet the below requirements: • No Data check: It is necessary to check what response does the system give when no data is submitted; • Valid data check: Examine the response when valid data is presented to the system; • Invalid data check: Examine the response when invalid data is presented to the system;

8. Illegal data format: Inspect the response when test data is presented in an invalid data format; • Boundary condition data set: Ensure that the test data complies the boundary value conditions; • Equivalence partition data set: Ensure that the test data meets the equivalence partition requirements; • Decision table data set: The set of test data should pass the decision table testing strategy; • State Transition test data set: The test data set should meet the transition test data strategy; • Use case test data: Ensure that the test data are in sync with the use-cases which you have planned to use. There are plenty of test generation tools available using which you can check the IT testenvironment management. Some of them are even customisable for different testing scenarios. Just make sure that the test data is well-designed so that it allows flawless testing.

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