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