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Modelling the ‘hurried’ bug report reading process to summarize bug reports

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Empirical Software Engineering Aims and scope Submit manuscript

Abstract

Although bug reports are frequently consulted project assets, they are communication logs, by-products of bug resolution, and not artifacts created with the intent of being easy to follow. To facilitate bug report digestion, we propose a new, unsupervised, bug report summarization approach that estimates the attention a user would hypothetically give to different sentences in a bug report, when pressed with time. We pose three hypotheses on what makes a sentence relevant: discussing frequently discussed topics, being evaluated or assessed by other sentences, and keeping focused on the bug report’s title and description. Our results suggest that our hypotheses are valid, since the summaries have as much as 12 % improvement in standard summarization evaluation metrics compared to the previous approach. Our evaluation also asks developers to assess the quality and usefulness of the summaries created for bug reports they have worked on. Feedback from developers not only shows the summaries are useful, but also points out important requirements for this, and any bug summarization approach, and indicates directions for future work.

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Notes

  1. http://www.debian.org/Bugs/server-control#summary

References

  • Ankolekar A, Sycara K, Herbsleb J, Kraut R, Welty C (2006) Supporting online problem-solving communities with the semantic web. WWW

  • Anvik J, Hiew L, C Murphy G (2006) Who should fix this bug? In: Proceedings of the 28th international conference on software engineering. ACM

  • Beineke P, Hastie T, Manning C (2004) Exploring sentiment summarization. AAAI

  • Bettenburg N, Just S, Schröter A, Weiss C, Premraj R, Zimmermann T (2008a) What makes a good bug report? SIGSOFT

  • Bettenburg N, Premraj R, Zimmermann T (2008b) Extracting structural information from bug reports. MSR

  • Blei DM, Ng Y, Jordan MI (2003) Latent dirichlet allocation. J Mach Learn Res

  • Boehm B, Basili VR (2001) Software defect reduction top 10 list. IEEE Comput:34

  • Breu S, Premraj R, Sillito J, Zimmermann T (2010) Information needs in bug reports: improving cooperation between developers and users. Comput Supported Coop Work

  • Brin S, Page L (1998) The anatomy of a large-scale hypertextual web search engine. WWW

  • Büttcher S, Clarke C, Cormack G (2010) Information retrieval: implementing and evaluating search engines. MIT Press

  • Dit B, Marcus A (2008) Improving the readability of defect reports. RSSE

  • Edmundson HP (1969) New methods in automatic extracting. J ACM (JACM) 16(2)

  • Gasser L, Ripoche G (2003) Distributed collective practices and free/open-source software problem management: perspectives and methods. CITE

  • Go A, Bhayani R (2009) Twitter sentiment classification using distant supervision. CS224N Project Report, Stanford

  • Haiduc S, Aponte J, Moreno L, Marcus A (2010) On the use of automated text summarization techniques for summarizing source code. In: 2010 17th working conference on reverse engineering (WCRE). IEEE

  • Hamou-Lhadj A, Lethbridge T (2006) Summarizing the content of large traces to facilitate the understanding of the behaviour of a software system. In: 14th IEEE international conference on program comprehension, 2006. ICPC 2006. IEEE

  • Hiew L (2006) Assisted detection of duplicate bug reports, Master’s thesis, The University of British Columbia

  • Hofmann T (1999) Probabilistic latent semantic indexing. In: SIGIR. ACM

  • Lloret E, Palomar M (2012) Text summarisation in progress: a literature review. Artif Intell Rev 37(1)

  • Lotufo R, Malik Z, Czarnecki K (2012a) Modelling the ‘hurried’ bug report reading process for bug report summarization. ICSM

  • Lotufo R, Passos L, Czarnecki K (2012b) Towards improving bug tracking systems with game mechanisms. MSR

  • Mani S, Catherine R, Sinha VS, Dubey A (2012) Ausum: approach for unsupervised bug report summarization. In: Proceedings of the ACM SIGSOFT 20th international symposium on the foundations of software engineering. ACM

  • Mann WC, Thompson SA (1988) Rhetorical structure theory: toward a functional theory of text organization. Text 8(3)

  • Menzies T, Marcus A (2008) Automated severity assessment of software defect reports. In: IEEE international conference on software maintenance, 2008. ICSM 2008. IEEE

  • Mihalcea R, Textrank PT (2004) Bringing order into texts. EMNLP

  • Murray G (2008) Summarizing spoken and written conversations. EMNLP

  • Nenkova A, Louis Ae (2008) Can you summarize this? Identifying correlates of input difficulty for generic multi-document summarization

  • Nenkova A, Passonneau R, McKeown K (2007) The pyramid method: Incorporating human content selection variation in summarization evaluation. ACM Trans Comput Logic

  • Porter MF et al (1980) An algorithm for suffix stripping

  • Quan X, Liu G, Lu Z, Ni X, Wenyin L (2009) Short text similarity based on probabilistic topics. Knowl Inf Syst

  • Radev DR (2004) Lexrank: graph-based lexical centrality as salience in text summarization. Artif Int

  • Rastkar S, Murphy GC, Murray G (2010) Summarizing software artifacts: a case study of bug reports. ICSE

  • Runeson P, AlexanderssonM, Nyholm O (2007) Detection of duplicate defect reports using natural language processing. In: Proceedings of the 29th international conference on software engineering

  • Sridhara G, Hill E, Muppaneni D, Pollock L, Vijay-Shanker K (2010) Towards automatically generating summary comments for java methods. In: Proceedings of the IEEE/ACM international conference on automated software engineering. ACM

  • Strauss A, Corbin J (2008) Basics of qualitative research: techniques and procedures for developing grounded theory. Sage Publications

  • Sun B,Mitra P, Giles CL, Yen J, Zha H (2007) Topic segmentation with shared topic detection and alignment of multiple documents. SIGIR

  • Tang H, Tan S, Cheng X (2009) A survey on sentiment detection of reviews. Exp Syst Appl

  • Thung F, Lo D, Jiang L (2012) Automatic defect categorization. In: 2012 19th working conference on reverse engineering (WCRE). IEEE

  • Tian Y, Lo D, Sun C (2012) Information retrieval based nearest neighbor classification for fine-grained bug severity prediction. In: 2012 19th working conference on reverse engineering (WCRE). IEEE

  • Wang X, Zhang L, Xie T, Anvik J, Sun J (2008) An approach to detecting duplicate bug reports using natural language and execution information. In: Proceedings of the 30th international conference on software engineering. ACM

  • Weiss C, Premraj R, Zimmermann T, Zeller A (2007) How long will it take to fix this bug? In: Proceedings of the 4th international workshop on mining software repositories. IEEE Computer Society

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Correspondence to Rafael Lotufo.

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Communicated by: Massimiliano Di Penta and Jonathan Maletic

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Lotufo, R., Malik, Z. & Czarnecki, K. Modelling the ‘hurried’ bug report reading process to summarize bug reports. Empir Software Eng 20, 516–548 (2015). https://doi.org/10.1007/s10664-014-9311-2

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  • DOI: https://doi.org/10.1007/s10664-014-9311-2

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