DocumentCode :
1634655
Title :
Striving for Failure: An Industrial Case Study about Test Failure Prediction
Author :
Anderson, Jeff ; Salem, Saeed ; Hyunsook Do
Volume :
2
fYear :
2015
Firstpage :
49
Lastpage :
58
Abstract :
Software regression testing is an important, yet very costly, part of most major software projects. When regression tests run, any failures that are found help catch bugs early and smooth the future development work. The act of executing large numbers of tests takes significant resources that could, otherwise, be applied elsewhere. If tests could be accurately classified as likely to pass or fail prior to the run, it could save significant time while maintaining the benefits of early bug detection. In this paper, we present a case study to build a classifier for regression tests based on industrial software, Microsoft Dynamics AX. In this study, we examine the effectiveness of this classification as well as which aspects of the software are the most important in predicting regression test failures.
Keywords :
pattern classification; program testing; regression analysis; software reliability; Microsoft Dynamics AX industrial software; early bug detection; regression test failure prediction; software classification; software projects; software regression testing; Complexity theory; History; Prediction algorithms; Predictive models; Software; Software engineering; Testing; Test failure prediction; case study; data-mining software repositories; regression testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering (ICSE), 2015 IEEE/ACM 37th IEEE International Conference on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/ICSE.2015.134
Filename :
7202949
Link To Document :
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