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Bug report recommendation for code inspection

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dc.contributor.author Fujiwara, Shin en
dc.contributor.author Hata, Hideaki en
dc.contributor.author Monden, Akito en
dc.contributor.author Matsumoto, Kenichi en
dc.date.accessioned 2018-10-30T04:57:14Z en
dc.date.available 2018-10-30T04:57:14Z en
dc.date.issued 2015 en
dc.identifier.uri http://hdl.handle.net/10061/12739 en
dc.description SWAN 2015 : 2015 IEEE 1st International Workshop on Software Analytics, 2 March 2015, Montreal, QC, Canada en
dc.description.abstract Large software projects such as Mozilla Firefox and Eclipse own more than ten thousand bug reports that have been reported but left unresolved. To utilize such a great amount of unresolved bug reports and accelerate bug detection and removal, we propose to a way recommend programmers a bug report that is likely to contain failure descriptions related to a source file being inspected. We employ the vector space model (VSM) to make a relevancy ranking of bug reports to a given source file. The result of an experiment using data of three open source software projects showed that the accuracies of recommendations ranged from 21.74% to 60.05% in terms of the percentage of recommendations that contained relevant bug reports in a top 10 recommended list. en
dc.language.iso en en
dc.publisher IEEE en
dc.rights c Copyright IEEE 2015 en
dc.subject program debugging en
dc.subject project management en
dc.subject public domain software en
dc.subject recommender systems en
dc.subject source code (software) en
dc.subject open source software projects en
dc.subject bug report relevancy ranking en
dc.subject VSM en
dc.subject vector space model en
dc.subject source file inspection en
dc.subject failure descriptions en
dc.subject bug removal en
dc.subject bug detection en
dc.subject Eclipse en
dc.subject Mozilla Firefox en
dc.subject code inspection en
dc.subject bug report recommendation en
dc.subject Inspection en
dc.subject Vectors en
dc.subject Computer bugs en
dc.subject Analytical models en
dc.subject Open source software en
dc.subject Data mining en
dc.title Bug report recommendation for code inspection en
dc.type.nii Conference Paper en
dc.textversion author en
dc.identifier.spage 9 en
dc.identifier.epage 12 en
dc.relation.doi 10.1109/SWAN.2015.7070481 en
dc.identifier.NAIST-ID 73299364 en
dc.identifier.NAIST-ID 73292310 en


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