Nothing Special   »   [go: up one dir, main page]

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 2006 Publication 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.
[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.
[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.
[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.
[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.
[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.
[7]
K. Fogel and M. Bar. Cross-Validatory Choice and Assessment of Statistical Predictions (with Discussion), volume 36.J. the Royal Statistical Soc., 1974.
[8]
K. Fogel and M. Bar.Open Source Development with CVS. Coriolis, 2001.
[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.
[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.
[11]
M. Kamkar. An overview and comparative classification of program slicing techniques. J. Syst. Softw., 31(3):197--214, 1995.
[12]
M. Lindvall and K. Sandahl. How well do experienced software developers predict software change? J. Syst. Softw., 43(1):19--27, 1998.
[13]
W. Miller and E. W. Myers. A file comparison program. Software Practice and Experience, 15(11):1025--1040, 1985.
[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.
[15]
S. L. Pfleeger. Software Engineering: Theory and Practice. Prentice-Hall, Upper Saddle River, NJ, 1998.
[16]
M. F. Porter. An algorithm for suffix stripping. Morgan Kaufmann Publishers Inc., 1997.
[17]
B. Ribeiro-neto and Baeza-yates. Modern Information Retrieval. Addison Wesley, 1999.
[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.
[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.
[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.
[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.

Cited By

View all
  • (2022)Retrieving data constraint implementations using fine-grained code patternsProceedings of the 44th International Conference on Software Engineering10.1145/3510003.3510167(1893-1905)Online publication date: 21-May-2022
  • (2022)Change-Patterns Mapping: A Boosting Way for Change Impact AnalysisIEEE Transactions on Software Engineering10.1109/TSE.2021.305948148:7(2376-2398)Online publication date: 1-Jul-2022
  • (2022)An Improvement to Test Case Prioritization Techniques Using Machine LearningProceedings of Third Doctoral Symposium on Computational Intelligence10.1007/978-981-19-3148-2_34(403-417)Online publication date: 10-Nov-2022
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

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
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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 May 2006

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. impact analysis
  2. mining software repositories

Qualifiers

  • Article

Conference

ICSE06
Sponsor:

Upcoming Conference

ICSE 2025

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)9
  • Downloads (Last 6 weeks)0
Reflects downloads up to 23 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2022)Retrieving data constraint implementations using fine-grained code patternsProceedings of the 44th International Conference on Software Engineering10.1145/3510003.3510167(1893-1905)Online publication date: 21-May-2022
  • (2022)Change-Patterns Mapping: A Boosting Way for Change Impact AnalysisIEEE Transactions on Software Engineering10.1109/TSE.2021.305948148:7(2376-2398)Online publication date: 1-Jul-2022
  • (2022)An Improvement to Test Case Prioritization Techniques Using Machine LearningProceedings of Third Doctoral Symposium on Computational Intelligence10.1007/978-981-19-3148-2_34(403-417)Online publication date: 10-Nov-2022
  • (2021)A systematic process for Mining Software Repositories: Results from a systematic literature reviewInformation and Software Technology10.1016/j.infsof.2021.106791(106791)Online publication date: Dec-2021
  • (2021)Traceability recovery between bug reports and test cases-a Mozilla Firefox case studyAutomated Software Engineering10.1007/s10515-021-00287-w28:2Online publication date: 7-Jul-2021
  • (2019)Key features recommendation to improve bug reportingProceedings of the International Conference on Software and System Processes10.1109/ICSSP.2019.00010(1-4)Online publication date: 25-May-2019
  • (2019)Identifying and predicting key features to support bug reportingJournal of Software: Evolution and Process10.1002/smr.218431:12Online publication date: 12-Dec-2019
  • (2018)An Integrated Model for Information Retrieval Based Change Impact AnalysisScientific Programming10.1155/2018/59136342018(5)Online publication date: 1-Mar-2018
  • (2018)BLIMP Tracer: Integrating Build Impact Analysis with Code Review2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)10.1109/ICSME.2018.00078(685-694)Online publication date: Sep-2018
  • (2018)Are Bug Reports Enough for Text Retrieval-Based Bug Localization?2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)10.1109/ICSME.2018.00046(381-392)Online publication date: Sep-2018
  • Show More Cited By

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media