Published: 11 Apr 2013
Conventional Software Testing Techniques That You Must Quit
Last Updated: 15 Jun 2020
Software development has a few important phases, namely requirement gathering, development, testing and installation on the end user’s systems. It is quite possible that bugs may get introduced into the software being developed during the development phase owing to human error.
Software testing is done prior to releasing any piece of code for installation on clients’ networks to avoid any erroneous execution, thereby ruining the user experience.
Software testing involves thorough testing of each and every component of the given software, right from user interface to the biggest as well as the minutest functionalities. It is essential that the testing team takes into account every single possible scenario into account while designing the test cases and tests the given software for each one of them thoroughly. What type of test data is being used by the test team has a major impact on the overall test process.
Test data is the data which is going to be used for testing a particular piece of software. While some data is used for obtaining confirmatory results, other data might be used for challenging the ability of the software. There are multiple ways in which appropriate test data can be obtained for testing a system. A tester or a program can produce the test data for testing a particular system.
For instance, the testing team may want to test whether the software provides the desired result or not. It would feed the data into the system and execute it. It would then analyze the result and decide if the expected results have been obtained. The software should at least deliver the intended results without any hiccup. After all, this was the basic purpose of creating it and it must fulfill that.
Conversely, it should not deliver unexpected, unusual or extreme results in case non standard input is passed to it. There must be sufficient test data management to test the negative scenario as well. This is to ensure that the software keeps performing smoothly even in case the end user enters wrong information while using it or chooses to do that deliberately in order to toy with the system.
Whether real production data or synthetic data should be used for testing purposes, experts are divided over it. There are specific scenarios in which each one of them fits the bill. For instance, in case of narrowly focused tests, synthetic data works better. However, production test data works better if close simulation of the real system is desired while testing. In many cases production data is duly masked before using it for testing.
In this way, the data being used for testing any system has a major forbearing on the overall results. After all, it is going to determine whether it is working as per expectations or not. Test teams ought to take into account this factor pretty seriously while devising test plans. Any slight error on this account can prove to be immensely costly for the overall project.