skip to main content
10.1145/1137983.1138009acmconferencesArticle/Chapter ViewAbstractPublication PagesicseConference Proceedingsconference-collections
Article

Fine grained indexing of software repositories to support impact analysis

Published:22 May 2006Publication History

ABSTRACT

Versioned and bug-tracked software systems provide a huge amount of historical data regarding source code changes and issues management. In this paper we deal with impact analysis of a change request and show that data stored in software repositories are a good descriptor on how past change requests have been resolved. A fine grained analysis method of software repositories is used to index code at different levels of granularity, such as lines of code and source files, with free text contained in software repositories. The method exploits information retrieval algorithms to link the change request description and code entities impacted by similar past change requests. We evaluate such approach on a set of three open-source projects.

References

  1. G. Antoniol, G. Canfora, G. Casazza, A. D. Lucia, and E. Merlo. Recovering traceability links between code and documentation. IEEE Trans. Softw. Eng., 28(10):970--983, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. R. S. Arnold and S. A. Bohner. Impact analysis - towards a framework for comparison. In ICSM '93: Proceedings of the Conference on Software Maintenance, pages 292--301. IEEE Computer Society, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. G. Canfora and L. Cerulo. Impact analysis by mining software and change request repositories. In METRICS '05: Proceedings of the 11th IEEE International Software Metrics Symposium. IEEE Computer Society, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. A. Chen, E. Chou, J. Wong, A. Y. Yao, Q. Zhang, S. Zhang, and A. Michail. CVSSearch: Searching through source code using CVS comments. In ICSM '01: Proceedings of 17th IEEE International Conference on Software Maintenance, page 364. IEEE Computer Society, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. F. Crestani, M. Lalmas, C. J. V. Rijsbergen, and I. Campbell. Is this document relevant?..probably: a survey of probabilistic models in information retrieval. ACM Comput. Surv., 30(4):528--552, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. M. Fischer, M. Pinzger, and H. Gall. Populating a release history database from version control and bug tracking systems. In ICSM '03: Proceedings of 19th IEEE International Conferenceon Software Maintenance, Amsterdam, Netherlands, Sept. 2003. IEEE Computer Society. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. K. Fogel and M. Bar. Cross-Validatory Choice and Assessment of Statistical Predictions (with Discussion), volume 36.J. the Royal Statistical Soc., 1974.Google ScholarGoogle Scholar
  8. K. Fogel and M. Bar.Open Source Development with CVS. Coriolis, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. A. E. Hassan and R. C. Holt. Predicting change propagation in software systems. In ICSM '04: Proceedings of the 20th IEEE International Conference on Software Maintenance, pages 284--293, Washington, DC, USA, 2004. IEEE Computer Society. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. K. S. Jones, S. Walker, and S. E. Robertson. A probabilistic model of information retrieval: development and comparative experiments. Inf. Process. Manage., 36(6):779--808, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. M. Kamkar. An overview and comparative classification of program slicing techniques. J. Syst. Softw., 31(3):197--214, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. M. Lindvall and K. Sandahl. How well do experienced software developers predict software change? J. Syst. Softw., 43(1):19--27, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. W. Miller and E. W. Myers. A file comparison program. Software Practice and Experience, 15(11):1025--1040, 1985.Google ScholarGoogle ScholarCross RefCross Ref
  14. M. Ohba and K. Gondow. Toward mining "concept keywords" from identifiers in large software projects. In IEEE 27th International Conference on Software Engineering - The 2nd International Workshop on Mining Software Repositories, pages 1--5, New York, NY, USA, 2005. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. S. L. Pfleeger. Software Engineering: Theory and Practice. Prentice-Hall, Upper Saddle River, NJ, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. M. F. Porter. An algorithm for suffix stripping. Morgan Kaufmann Publishers Inc., 1997.Google ScholarGoogle Scholar
  17. B. Ribeiro-neto and Baeza-yates. Modern Information Retrieval. Addison Wesley, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. A. T. T. Ying, G. C. Murphy, R. Ng, and M. C. Chu-Carroll. Predicting source code changes by mining revision history. IEEE Transactions on Software Engineering, 30:574--586, Sept.2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. A. T. T. Ying, J. L. Wright, and S. Abrams. Source code that talks: an exploration of eclipse task comments and their implication to repository mining. In IEEE 27th International Conference on Software Engineering - The 2nd International Workshop on Mining Software Repositories, pages 1--5, New York, NY, USA, 2005. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. T. Zimmermann, P. Weisgerber, S. Diehl, and A. Zeller. Mining version histories to guide software changes. In ICSE '04: Proceedings of the 26th International Conference on Software Engineering, pages 563--572. IEEE Computer Society, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. T. Zimmermann and P. Weißgerber. Preprocessing CVS data for fine-grained analysis. In IEEE 26th International Conference on Software Engineering - The 1st International Workshop on Mining Software Repositories, pages 2--6,2004.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Fine grained indexing of software repositories to support impact analysis

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          MSR '06: Proceedings of the 2006 international workshop on Mining software repositories
          May 2006
          191 pages
          ISBN:1595933972
          DOI:10.1145/1137983

          Copyright © 2006 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 22 May 2006

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • Article

          Upcoming Conference

          ICSE 2025

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader