Abstract
Traceability links between requirements and source code can assist in software maintenance tasks. There are some automatic traceability recovery methods. Most of them are similarity-based methods recovering links by comparing representation similarity between requirements and code. They cannot work well if there are some links independent of the representation similarity. Herein to cover weakness of them and improve the accuracy of recovery, we propose a method that extends the similarity-based method using two techniques: a log-based traceability recovery method using the configuration management log and a link recommendation from user feedback. These techniques are independent of the representation similarity between requirements and code. As a result of applying our method to a large enterprise system, we successfully improved both recall and precision by more than a 20 percent point in comparison with singly applying the similarity-based method (recall: 60.2% to 80.4%, precision: 41.1% to 64.8%).
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Publisher | Springer Verlag |
| Pages | 247-262 |
| Number of pages | 16 |
| Volume | 9097 |
| ISBN (Print) | 9783319190686 |
| DOIs | |
| Publication status | Published - 2015 |
| Event | 27th International Conference on Advanced Information Systems Engineering, CAiSE 2015 - Stockholm, Sweden Duration: 2015 Jun 8 → 2015 Jun 12 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 9097 |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 27th International Conference on Advanced Information Systems Engineering, CAiSE 2015 |
|---|---|
| Country | Sweden |
| City | Stockholm |
| Period | 15/6/8 → 15/6/12 |
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Keywords
- Configuration management log
- Interactive method
- Traceability
ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science
Cite this
Interactive recovery of requirements traceability links using user feedback and configuration management logs. / Tsuchiya, Ryosuke; Washizaki, Hironori; Fukazawa, Yoshiaki; Oshima, Keishi; Mibe, Ryota.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9097 Springer Verlag, 2015. p. 247-262 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9097).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Interactive recovery of requirements traceability links using user feedback and configuration management logs
AU - Tsuchiya, Ryosuke
AU - Washizaki, Hironori
AU - Fukazawa, Yoshiaki
AU - Oshima, Keishi
AU - Mibe, Ryota
PY - 2015
Y1 - 2015
N2 - Traceability links between requirements and source code can assist in software maintenance tasks. There are some automatic traceability recovery methods. Most of them are similarity-based methods recovering links by comparing representation similarity between requirements and code. They cannot work well if there are some links independent of the representation similarity. Herein to cover weakness of them and improve the accuracy of recovery, we propose a method that extends the similarity-based method using two techniques: a log-based traceability recovery method using the configuration management log and a link recommendation from user feedback. These techniques are independent of the representation similarity between requirements and code. As a result of applying our method to a large enterprise system, we successfully improved both recall and precision by more than a 20 percent point in comparison with singly applying the similarity-based method (recall: 60.2% to 80.4%, precision: 41.1% to 64.8%).
AB - Traceability links between requirements and source code can assist in software maintenance tasks. There are some automatic traceability recovery methods. Most of them are similarity-based methods recovering links by comparing representation similarity between requirements and code. They cannot work well if there are some links independent of the representation similarity. Herein to cover weakness of them and improve the accuracy of recovery, we propose a method that extends the similarity-based method using two techniques: a log-based traceability recovery method using the configuration management log and a link recommendation from user feedback. These techniques are independent of the representation similarity between requirements and code. As a result of applying our method to a large enterprise system, we successfully improved both recall and precision by more than a 20 percent point in comparison with singly applying the similarity-based method (recall: 60.2% to 80.4%, precision: 41.1% to 64.8%).
KW - Configuration management log
KW - Interactive method
KW - Traceability
UR - http://www.scopus.com/inward/record.url?scp=84937469415&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84937469415&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-19069-3_16
DO - 10.1007/978-3-319-19069-3_16
M3 - Conference contribution
AN - SCOPUS:84937469415
SN - 9783319190686
VL - 9097
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 247
EP - 262
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PB - Springer Verlag
ER -