Article

Fine grained indexing of software repositories to support impact analysis

Authors:

Gerardo Canfora,

Luigi CeruloAuthors Info & Claims

MSR '06: Proceedings of the 2006 international workshop on Mining software repositories

Pages 105 - 111

https://doi.org/10.1145/1137983.1138009

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.

Digital 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.

Digital 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.

Digital 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.

Digital 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.

Digital 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.

Digital 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.

[8]

K. Fogel and M. Bar.Open Source Development with CVS. Coriolis, 2001.

Digital 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.

Digital 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.

Digital Library

[11]

M. Kamkar. An overview and comparative classification of program slicing techniques. J. Syst. Softw., 31(3):197--214, 1995.

Digital Library

[12]

M. Lindvall and K. Sandahl. How well do experienced software developers predict software change? J. Syst. Softw., 43(1):19--27, 1998.

Digital Library

[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.

Digital Library

[15]

S. L. Pfleeger. Software Engineering: Theory and Practice. Prentice-Hall, Upper Saddle River, NJ, 1998.

Digital Library

[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.

Digital 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.

Digital 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.

Digital 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.

Digital 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.

Cited By

Florez JPerry JWei SMarcus ADwyer MDamian DZeller A(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
https://dl.acm.org/doi/10.1145/3510003.3510167
Huang YJiang JLuo XChen XZheng ZJia NHuang G(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
https://doi.org/10.1109/TSE.2021.3059481
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Fine grained indexing of software repositories to support impact analysis

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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

General Chairs:
Stephan Diehl
University Trier, Germany
,
Harald Gall
University of Zurich, Switzerland
,
Ahmed E. Hassan
Research in Motion RIM, Canada

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]

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Published: 22 May 2006

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May 22 - 23, 2006

Shanghai, China

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Cited By

Florez JPerry JWei SMarcus ADwyer MDamian DZeller A(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
https://dl.acm.org/doi/10.1145/3510003.3510167
Huang YJiang JLuo XChen XZheng ZJia NHuang G(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
https://doi.org/10.1109/TSE.2021.3059481
khan SPal S(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
https://doi.org/10.1007/978-981-19-3148-2_34
Vidoni M(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
https://doi.org/10.1016/j.infsof.2021.106791
Gadelha GRamalho FMassoni T(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
https://doi.org/10.1007/s10515-021-00287-w
Rejaul KSutton SArmbrust OHebig R(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
https://dl.acm.org/doi/10.1109/ICSSP.2019.00010
Karim MIhara AChoi EIida H(2019)Identifying and predicting key features to support bug reportingJournal of Software: Evolution and Process10.1002/smr.218431:12Online publication date: 12-Dec-2019
https://dl.acm.org/doi/10.1002/smr.2184
Wang WHe YLi TZhu JLiu J(2018)An Integrated Model for Information Retrieval Based Change Impact AnalysisScientific Programming10.1155/2018/59136342018(5)Online publication date: 1-Mar-2018
https://dl.acm.org/doi/10.1155/2018/5913634
Wen RGilbert DRoche MMcIntosh S(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
https://doi.org/10.1109/ICSME.2018.00078
Mills CPantiuchina JParra EBavota GHaiduc S(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
https://doi.org/10.1109/ICSME.2018.00046
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