Interactive recovery of requirements traceability links using user feedback and configuration management logs

Ryosuke Tsuchiya, Hironori Washizaki, Yoshiaki Fukazawa, Keishi Oshima, Ryota Mibe

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    6 Citations (Scopus)

    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 languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    PublisherSpringer Verlag
    Pages247-262
    Number of pages16
    Volume9097
    ISBN (Print)9783319190686
    DOIs
    Publication statusPublished - 2015
    Event27th International Conference on Advanced Information Systems Engineering, CAiSE 2015 - Stockholm, Sweden
    Duration: 2015 Jun 82015 Jun 12

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume9097
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other27th International Conference on Advanced Information Systems Engineering, CAiSE 2015
    CountrySweden
    CityStockholm
    Period15/6/815/6/12

    Fingerprint

    Traceability
    Recovery
    Feedback
    Configuration
    Requirements
    Computer software maintenance
    Software Maintenance
    Industry
    Percent
    Similarity
    Recommendations
    Cover

    Keywords

    • Configuration management log
    • Interactive method
    • Traceability

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

    Cite this

    Tsuchiya, R., Washizaki, H., Fukazawa, Y., Oshima, K., & Mibe, R. (2015). Interactive recovery of requirements traceability links using user feedback and configuration management logs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9097, pp. 247-262). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9097). Springer Verlag. https://doi.org/10.1007/978-3-319-19069-3_16

    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 proceedingConference contribution

    Tsuchiya, R, Washizaki, H, Fukazawa, Y, Oshima, K & Mibe, R 2015, Interactive recovery of requirements traceability links using user feedback and configuration management logs. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 9097, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9097, Springer Verlag, pp. 247-262, 27th International Conference on Advanced Information Systems Engineering, CAiSE 2015, Stockholm, Sweden, 15/6/8. https://doi.org/10.1007/978-3-319-19069-3_16
    Tsuchiya R, Washizaki H, Fukazawa Y, Oshima K, Mibe R. Interactive recovery of requirements traceability links using user feedback and configuration management logs. In 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)). https://doi.org/10.1007/978-3-319-19069-3_16
    Tsuchiya, Ryosuke ; Washizaki, Hironori ; Fukazawa, Yoshiaki ; Oshima, Keishi ; Mibe, Ryota. / Interactive recovery of requirements traceability links using user feedback and configuration management logs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9097 Springer Verlag, 2015. pp. 247-262 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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    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{\%}).",
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