WHOSEFAULT: Automatic Developer-to-Fault Assignment through Fault Localization.
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| Title: | WHOSEFAULT: Automatic Developer-to-Fault Assignment through Fault Localization. |
|---|---|
| Authors: | Servant, Francisco1 fservant@ics.uci.edu, Jones, James A.1 jajones@ics.uci.edu |
| Source: | ICSE: International Conference on Software Engineering. Feb2012, p36-46. 11p. |
| Subjects: | Computer system failure prevention, Computer software developers, Software localization, Data mining, Computer diagnostic software |
| Abstract: | This paper describes a new technique, which automatically selects the most appropriate developers for fixing the fault represented by a failing test case, and provides a diagnosis of where to look for the fault. This technique works by incorporating three key components: (1) fault localization to inform locations whose execution correlate with failure, (2) history mining to inform which developers edited each line of code and when, and (3) expertise assignment to map locations to developers. To our knowledge, the technique is the first to assign developers to execution failures, without the need for textual bug reports. We implement this technique in our tool, WHOSEFAULT, and describe an experiment where we utilize a large, open-source project to determine the frequency in which our tool suggests an assignment to the actual developer who fixed the fault. Our results show that 81% of the time, WHOSEFAULT produced the same developer that actually fixed the fault within the top three suggestions. We also show that our technique improved by a difference between 4% and 40% the results of a baseline technique. Finally, we explore the influence of each of the three components of our technique over its results, and compare our expertise algorithm against an existing expertise assessment technique and find that our algorithm provides greater accuracy, by up to 37%. [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.) | |
| Database: | Engineering Source |
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| Items | – Name: Title Label: Title Group: Ti Data: WHOSEFAULT: Automatic Developer-to-Fault Assignment through Fault Localization. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Servant%2C+Francisco%22">Servant, Francisco</searchLink><relatesTo>1</relatesTo><i> fservant@ics.uci.edu</i><br /><searchLink fieldCode="AR" term="%22Jones%2C+James+A%2E%22">Jones, James A.</searchLink><relatesTo>1</relatesTo><i> jajones@ics.uci.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22ICSE%3A+International+Conference+on+Software+Engineering%22">ICSE: International Conference on Software Engineering</searchLink>. Feb2012, p36-46. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+system+failure+prevention%22">Computer system failure prevention</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software+developers%22">Computer software developers</searchLink><br /><searchLink fieldCode="DE" term="%22Software+localization%22">Software localization</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining%22">Data mining</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+diagnostic+software%22">Computer diagnostic software</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper describes a new technique, which automatically selects the most appropriate developers for fixing the fault represented by a failing test case, and provides a diagnosis of where to look for the fault. This technique works by incorporating three key components: (1) fault localization to inform locations whose execution correlate with failure, (2) history mining to inform which developers edited each line of code and when, and (3) expertise assignment to map locations to developers. To our knowledge, the technique is the first to assign developers to execution failures, without the need for textual bug reports. We implement this technique in our tool, WHOSEFAULT, and describe an experiment where we utilize a large, open-source project to determine the frequency in which our tool suggests an assignment to the actual developer who fixed the fault. Our results show that 81% of the time, WHOSEFAULT produced the same developer that actually fixed the fault within the top three suggestions. We also show that our technique improved by a difference between 4% and 40% the results of a baseline technique. Finally, we explore the influence of each of the three components of our technique over its results, and compare our expertise algorithm against an existing expertise assessment technique and find that our algorithm provides greater accuracy, by up to 37%. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab 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: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 36 Subjects: – SubjectFull: Computer system failure prevention Type: general – SubjectFull: Computer software developers Type: general – SubjectFull: Software localization Type: general – SubjectFull: Data mining Type: general – SubjectFull: Computer diagnostic software Type: general Titles: – TitleFull: WHOSEFAULT: Automatic Developer-to-Fault Assignment through Fault Localization. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Servant, Francisco – PersonEntity: Name: NameFull: Jones, James A. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2012 Type: published Y: 2012 Titles: – TitleFull: ICSE: International Conference on Software Engineering Type: main |
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