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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 |
