skip to main content
10.5555/2486788.2486959acmconferencesArticle/Chapter ViewAbstractPublication PagesicseConference Proceedingsconference-collections
research-article

Why did this code change?

Published: 18 May 2013 Publication History

Abstract

When a developer works on code that is shared with other developers, she needs to know why the code has been changed in particular ways to avoid reintroducing bugs. A developer looking at a code change may have access to a short commit message or a link to a bug report which may provide detailed information about how the code changed but which often lacks information about what motivated the change. This motivational information can sometimes be found by piecing together information from a set of relevant project documents, but few developers have the time to find and read the right documentation. We propose the use of multi-document summarization techniques to generate a concise natural language description of why code changed so that a developer can choose the right course of action.

References

[1]
G. Carenini, R. Ng, and X. Zhou, “Summarizing email conversations with clue words,” in WWW’07: Proc. of the 16th International World Wide Web conf., 2007, pp. 91–100.
[2]
S. Wan and K. McKeown, “Generating overview summaries of ongoing email thread discussions,” in COLING’04: Proc. of the 20th International conf. on Computational Linguistics, 2004, pp. 549–556.
[3]
R. Lotufo, Z. Malik, and K. Czarnecki, “Modelling the ‘hurried’ bug report reading process to summarize bug reports,” in ICSM’12: Proc. of the 28th International conf. on Software Maintenance, 2012.
[4]
D. Radev, T. Allison, S. Blair-Goldensohn, J. Blitzer, A. Celebi, S. Dimitrov, E. Drabek, A. Hakim, W. Lam, D. Liu et al., “MEAD-a platform for multidocument multilingual text summarization,” in LREC’04: Proc. of the International conf. on Language Resources and Evaluation, 2004.
[5]
Y.-W. Chen and C.-J. Lin, “Combining SVMs with various feature selection strategies,” in Feature extraction, foundations and applications. Springer, 2006, pp. 315–324.
[6]
B. Fluri, M. Wursch, M. Pinzger, and H. Gall, “Change distilling:tree differencing for fine-grained source code change extraction,” Software Engineering, IEEE Trans. on, vol. 33, no. 11, pp. 725 –743, nov. 2007.
[7]
R. Purushothaman and D. Perry, “Toward understanding the rhetoric of small source code changes,” Software Engineering, IEEE Transactions on, vol. 31, no. 6, pp. 511 – 526, june 2005.
[8]
S. L. Voinea, A. Telea, and M. Chaudron, “CVSscan: Visualization of code evolution,” in Softviz’05: Proc. of the 2005 ACM Symposium on Software Visualization, 2005, pp. 47–56.
[9]
S. Haiduc, J. Aponte, L. Moreno, and A. Marcus, “On the use of automated text summarization techniques for summarizing source code,” in WCRE’10: Proc. of the 17th Working conf. on Reverse Engineering, 2010, pp. 35–44.
[10]
G. Sridhara, E. Hill, D. Muppaneni, L. Pollock, and K. Vijay-Shanker, “Towards automatically generating summary comments for java methods,” in ASE’10: Proc. of the 25th international conf. on Automated software engineering, 2010, pp. 43–52.
[11]
S. Rastkar, G. Murphy, and A. Bradley, “Generating natural language summaries for crosscutting source code concerns,” in ICSM’11: Proc. of the 27th International conf. on Software Maintenance, 2011, pp. 103– 112.
[12]
S. Rastkar, G. C. Murphy, and G. Murray, “Summarizing software artifacts: a case study of bug reports,” in ICSE’10: Proc. of the 32nd International conf. on Software Engineering, 2010, pp. 505–514.
[13]
X. Wan and J. Yang, “Multi-document summarization using clusterbased link analysis,” in SIGIR’08: Proc. of the 31st annual international ACM SIGIR conf. on research and development in information retrieval, 2008, pp. 299–306.
[14]
G. Erkan and D. Radev, “Lexpagerank: Prestige in multi-document text summarization,” in EMNLP’04: Proc. of the 2004 conf. on Empirical Methods on Natural Language Processing, 2004, pp. 365–371.
[15]
A. D. Lucia, F. Fasano, R. Oliveto, and G. Tortora, “Recovering traceability links in software artifact management systems using information retrieval methods,” ACM Trans. Softw. Eng. Methodol., vol. 16, no. 4, Sep. 2007.
[16]
4 www.eclipse.org/mylyn, verified 12/12/12

Cited By

View all
  • (2021)Can Program Synthesis be Used to Learn Merge Conflict Resolutions?Proceedings of the 43rd International Conference on Software Engineering10.1109/ICSE43902.2021.00077(785-796)Online publication date: 22-May-2021
  • (2019)Decomposing the rationale of code commits: the software developer’s perspectiveProceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3338906.3338979(397-408)Online publication date: 12-Aug-2019
  • (2018)ClDiff: generating concise linked code differencesProceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering10.1145/3238147.3238219(679-690)Online publication date: 3-Sep-2018
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
ICSE '13: Proceedings of the 2013 International Conference on Software Engineering
May 2013
1561 pages
ISBN:9781467330763

Sponsors

Publisher

IEEE Press

Publication History

Published: 18 May 2013

Check for updates

Qualifiers

  • Research-article

Conference

ICSE '13
Sponsor:

Acceptance Rates

Overall Acceptance Rate 276 of 1,856 submissions, 15%

Upcoming Conference

ICSE 2025

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)6
  • Downloads (Last 6 weeks)1
Reflects downloads up to 05 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2021)Can Program Synthesis be Used to Learn Merge Conflict Resolutions?Proceedings of the 43rd International Conference on Software Engineering10.1109/ICSE43902.2021.00077(785-796)Online publication date: 22-May-2021
  • (2019)Decomposing the rationale of code commits: the software developer’s perspectiveProceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3338906.3338979(397-408)Online publication date: 12-Aug-2019
  • (2018)ClDiff: generating concise linked code differencesProceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering10.1145/3238147.3238219(679-690)Online publication date: 3-Sep-2018
  • (2018)Neural-machine-translation-based commit message generation: how far are we?Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering10.1145/3238147.3238190(373-384)Online publication date: 3-Sep-2018
  • (2018)Decision knowledge triggers in continuous software engineeringProceedings of the 4th International Workshop on Rapid Continuous Software Engineering10.1145/3194760.3194765(23-26)Online publication date: 29-May-2018
  • (2017)Automatically generating commit messages from diffs using neural machine translationProceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering10.5555/3155562.3155583(135-146)Online publication date: 30-Oct-2017
  • (2017)ARENAIEEE Transactions on Software Engineering10.1109/TSE.2016.259153643:2(106-127)Online publication date: 1-Feb-2017
  • (2017)How developers document pull requests with external referencesProceedings of the 25th International Conference on Program Comprehension10.1109/ICPC.2017.30(23-33)Online publication date: 20-May-2017
  • (2017)Towards automatic generation of short summaries of commitsProceedings of the 25th International Conference on Program Comprehension10.1109/ICPC.2017.12(320-323)Online publication date: 20-May-2017
  • (2017)Mining version control system for automatically generating commit commentProceedings of the 11th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1109/ESEM.2017.56(414-423)Online publication date: 9-Nov-2017
  • 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