An Empirical Study of Regression Test Application Frequency
Jung-Min Kim; Porter, A.; Rothermel, G.
Page(s): 126 135
Proceedings of the 22nd International Conference on Software Engineering, 2000. ICSE 2000
Regression testing is an expensive maintenance process used to revalidate modified software. Regression test selection (RTS) techniques try to lower the cost of regression testing by selecting and running a subset of all existing test cases. The authors of the paper believe that issues such as the frequency with which testing is done have a strong effect on the behavior of these techniques. Therefore, they conducted an experiment to assess the effects of test application frequency on the cost and benefits of regression test selection techniques. Their results expose essential tradeoffs that should be considered when using these techniques over a series of software releases.
Keywords: regression testing, application frequency, empirical study
After modifying software, developers typically want to know that unmodified code has not been adversely affected. When such unmodified code is adversely affected, we say that regression error has occurred.
Regression test selection (RTS) technique has been proposed to reduce regression testing cost. With this approach, only a subset of test cases are selected and rerun.
The cost-benefit tradeoffs of RTS techniques is a central concern of regression testing research and techniques since in general, optimal test selection (i.e. selecting exactly the fault revealing test cases) is impossible.
A common way to study this problem has been to find or create a base and modified versions of a system and accompanying test suites. Next, a test selection algorithm is run and the size and effectiveness of the selected test suite is compared to the size and effectiveness of the original test... [continues]
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