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Striving for Failure: An Industrial Case Study About Test Failure Prediction.

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Title: Striving for Failure: An Industrial Case Study About Test Failure Prediction.
Authors: Anderson, Jeff1 jeffrey.r.anderson@ndsu.edu, Salem, Saeed2 saeed.salem@ndsu.edu, Hyunsook Do2 hyunsook.do@ndsu.edu
Source: ICSE: International Conference on Software Engineering. 2015, p49-58. 10p.
Subjects: Computer software research, Regression analysis, Microsoft software, Computer files, Computer systems
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. [ABSTRACT FROM AUTHOR]
Copyright of ICSE: International Conference on Software Engineering is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Striving for Failure: An Industrial Case Study About Test Failure Prediction.
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  Data: <searchLink fieldCode="AR" term="%22Anderson%2C+Jeff%22">Anderson, Jeff</searchLink><relatesTo>1</relatesTo><i> jeffrey.r.anderson@ndsu.edu</i><br /><searchLink fieldCode="AR" term="%22Salem%2C+Saeed%22">Salem, Saeed</searchLink><relatesTo>2</relatesTo><i> saeed.salem@ndsu.edu</i><br /><searchLink fieldCode="AR" term="%22Hyunsook+Do%22">Hyunsook Do</searchLink><relatesTo>2</relatesTo><i> hyunsook.do@ndsu.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22ICSE%3A+International+Conference+on+Software+Engineering%22">ICSE: International Conference on Software Engineering</searchLink>. 2015, p49-58. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Computer+software+research%22">Computer software research</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Microsoft+software%22">Microsoft software</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+files%22">Computer files</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+systems%22">Computer systems</searchLink>
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  Data: 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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of ICSE: International Conference on Software Engineering is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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        Value: 10.1109/ICSE.2015.134
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      – Code: eng
        Text: English
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        PageCount: 10
        StartPage: 49
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      – SubjectFull: Computer software research
        Type: general
      – SubjectFull: Regression analysis
        Type: general
      – SubjectFull: Microsoft software
        Type: general
      – SubjectFull: Computer files
        Type: general
      – SubjectFull: Computer systems
        Type: general
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      – TitleFull: Striving for Failure: An Industrial Case Study About Test Failure Prediction.
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            NameFull: Anderson, Jeff
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            NameFull: Salem, Saeed
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            NameFull: Hyunsook Do
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              Text: 2015
              Type: published
              Y: 2015
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            – TitleFull: ICSE: International Conference on Software Engineering
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