Automatic summarization of open-domain multiparty dialogues in diverse genres
Computational Linguistics - Summarization
Hipikat: recommending pertinent software development artifacts
Proceedings of the 25th International Conference on Software Engineering
Coping with an open bug repository
eclipse '05 Proceedings of the 2005 OOPSLA workshop on Eclipse technology eXchange
Proceedings of the 28th international conference on Software engineering
A Linguistic Analysis of How People Describe Software Problems
VLHCC '06 Proceedings of the Visual Languages and Human-Centric Computing
Generating overview summaries of ongoing email thread discussions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Detection of Duplicate Defect Reports Using Natural Language Processing
ICSE '07 Proceedings of the 29th international conference on Software Engineering
An approach to detecting duplicate bug reports using natural language and execution information
Proceedings of the 30th international conference on Software engineering
Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering
Summarizing spoken and written conversations
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
The AMI meeting corpus: a pre-announcement
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 2
Improving traceability link recovery methods through software artifact summarization
Proceedings of the 6th International Workshop on Traceability in Emerging Forms of Software Engineering
Mining whining in support forums with frictionary
CHI '12 Extended Abstracts on Human Factors in Computing Systems
Developer prioritization in bug repositories
Proceedings of the 34th International Conference on Software Engineering
Content classification of development emails
Proceedings of the 34th International Conference on Software Engineering
Concept location using formal concept analysis and information retrieval
ACM Transactions on Software Engineering and Methodology (TOSEM)
AUSUM: approach for unsupervised bug report summarization
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
An Information Foraging Theory Perspective on Tools for Debugging, Refactoring, and Reuse Tasks
ACM Transactions on Software Engineering and Methodology (TOSEM)
More testers - The effect of crowd size and time restriction in software testing
Information and Software Technology
Facilitating developer-user interactions with mobile app review digests
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Proceedings of the 2013 International Conference on Software Engineering
Deciphering the story of software development through frequent pattern mining
Proceedings of the 2013 International Conference on Software Engineering
Bug resolution catalysts: identifying essential non-committers from bug repositories
Proceedings of the 10th Working Conference on Mining Software Repositories
Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering
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Many software artifacts are created, maintained and evolved as part of a software development project. As software developers work on a project, they interact with existing project artifacts, performing such activities as reading previously filed bug reports in search of duplicate reports. These activities often require a developer to peruse a substantial amount of text. In this paper, we investigate whether it is possible to summarize software artifacts automatically and effectively so that developers could consult smaller summaries instead of entire artifacts. To provide focus to our investigation, we consider the generation of summaries for bug reports. We found that existing conversation-based generators can produce better results than random generators and that a generator trained specifically on bug reports can perform statistically better than existing conversation-based generators. We demonstrate that humans also find these generated summaries reasonable indicating that summaries might be used effectively for many tasks.