Integrated Impact Analysis for Managing Software Changes.
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| Title: | Integrated Impact Analysis for Managing Software Changes. |
|---|---|
| Authors: | Gethers, Malcom1 mgethers@cs.wm.edu, Dit, Bogdan1 bdit@cs.wm.edu, Kagdi, Huzefa2 kagdi@cs.wichita.edu, Poshyvanyk, Denys1 denys@cs.wm.edu |
| Source: | ICSE: International Conference on Software Engineering. Feb2012, p430-440. 11p. |
| Subjects: | Computer software development, Computer programming management, Debugging, Electronic data processing, Execution traces (Computer program testing), Information retrieval |
| Abstract: | The paper presents an adaptive approach to perform impact analysis from a given change request to source code. Given a textual change request (e.g., a bug report), a single snapshot (release) of source code, indexed using Latent Semantic Indexing, is used to estimate the impact set. Should additional contextual information be available, the approach configures the best-fit combination to produce an improved impact set. Contextual information includes the execution trace and an initial source code entity verified for change. Combinations of information retrieval, dynamic analysis, and data mining of past source code commits are considered. The research hypothesis is that these combinations help counter the precision or recall deficit of individual techniques and improve the overall accuracy. The tandem operation of the three techniques sets it apart from other related solutions. Automation along with the effective utilization of two key sources of developer knowledge, which are often overlooked in impact analysis at the change request level, is achieved. To validate our approach, we conducted an empirical evaluation on four open source software systems. A benchmark consisting of a number of maintenance issues, such as feature requests and bug fixes, and their associated source code changes was established by manual examination of these systems and their change history. Our results indicate that there are combinations formed from the augmented developer contextual information that show statistically significant improvement over stand-alone approaches. [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 |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Integrated Impact Analysis for Managing Software Changes. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Gethers%2C+Malcom%22">Gethers, Malcom</searchLink><relatesTo>1</relatesTo><i> mgethers@cs.wm.edu</i><br /><searchLink fieldCode="AR" term="%22Dit%2C+Bogdan%22">Dit, Bogdan</searchLink><relatesTo>1</relatesTo><i> bdit@cs.wm.edu</i><br /><searchLink fieldCode="AR" term="%22Kagdi%2C+Huzefa%22">Kagdi, Huzefa</searchLink><relatesTo>2</relatesTo><i> kagdi@cs.wichita.edu</i><br /><searchLink fieldCode="AR" term="%22Poshyvanyk%2C+Denys%22">Poshyvanyk, Denys</searchLink><relatesTo>1</relatesTo><i> denys@cs.wm.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, p430-440. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+software+development%22">Computer software development</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+programming+management%22">Computer programming management</searchLink><br /><searchLink fieldCode="DE" term="%22Debugging%22">Debugging</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Execution+traces+%28Computer+program+testing%29%22">Execution traces (Computer program testing)</searchLink><br /><searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The paper presents an adaptive approach to perform impact analysis from a given change request to source code. Given a textual change request (e.g., a bug report), a single snapshot (release) of source code, indexed using Latent Semantic Indexing, is used to estimate the impact set. Should additional contextual information be available, the approach configures the best-fit combination to produce an improved impact set. Contextual information includes the execution trace and an initial source code entity verified for change. Combinations of information retrieval, dynamic analysis, and data mining of past source code commits are considered. The research hypothesis is that these combinations help counter the precision or recall deficit of individual techniques and improve the overall accuracy. The tandem operation of the three techniques sets it apart from other related solutions. Automation along with the effective utilization of two key sources of developer knowledge, which are often overlooked in impact analysis at the change request level, is achieved. To validate our approach, we conducted an empirical evaluation on four open source software systems. A benchmark consisting of a number of maintenance issues, such as feature requests and bug fixes, and their associated source code changes was established by manual examination of these systems and their change history. Our results indicate that there are combinations formed from the augmented developer contextual information that show statistically significant improvement over stand-alone approaches. [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: 430 Subjects: – SubjectFull: Computer software development Type: general – SubjectFull: Computer programming management Type: general – SubjectFull: Debugging Type: general – SubjectFull: Electronic data processing Type: general – SubjectFull: Execution traces (Computer program testing) Type: general – SubjectFull: Information retrieval Type: general Titles: – TitleFull: Integrated Impact Analysis for Managing Software Changes. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Gethers, Malcom – PersonEntity: Name: NameFull: Dit, Bogdan – PersonEntity: Name: NameFull: Kagdi, Huzefa – PersonEntity: Name: NameFull: Poshyvanyk, Denys 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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