Techniques |
Applicability |
TCP
TCS
|
Industry Motivation
Industry Evaluation
Practitioner Feedback
|
Experiment subject(s) |
Industrial Partner |
Programming Language |
Dataset from Terravis (375 TCs)
Industrial proprietary, small scale (in number of tests, long execution time) |
Terravis (Switzerland) |
WS-BPEL 2.0 |
Effectiveness Metrics |
Efficiency Metrics |
Other Metrics |
Coverage Effectiveness (CE), Accumulated regression risk
|
|
|
Information Approach |
Algorithm Approach |
Open Challenges |
Coverage-based
|
|
combine with other TCP/TCS strategies; study differences between minor and major releases w.r.t. regression risk.
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Abstract
Regression Testing is an important quality assurance activity for combating unwanted side-effects, which might have been introduced in a new software release. Selecting and prioritizing regression test cases is a challenge in practice – especially in a world of ever increasing complex- ity, distribution, and size of the software solutions. Current approaches try to minimize the number of regression test cases by analyzing the change and the coverage of the tests with regards to this change. Our approach utilizes usage frequencies from the previous, productive soft- ware version in order to select or prioritize test cases by calculating the Regression Risk of a change. This takes into account that not all features of a software are used the same. We successfully validate our approach in a case study of an industry project which develops a complex process integration platform.