KEA: practical automatic keyphrase extraction
Proceedings of the fourth ACM conference on Digital libraries
Recovering Traceability Links between Code and Documentation
IEEE Transactions on Software Engineering
Recovering documentation-to-source-code traceability links using latent semantic indexing
Proceedings of the 25th International Conference on Software Engineering
Traceability Recovery by Modeling Programmer Behavior
WCRE '00 Proceedings of the Seventh Working Conference on Reverse Engineering (WCRE'00)
Improving Requirements Tracing via Information Retrieval
RE '03 Proceedings of the 11th IEEE International Conference on Requirements Engineering
Supporting Software Evolution through Dynamically Retrieving Traces to UML Artifacts
IWPSE '04 Proceedings of the Principles of Software Evolution, 7th International Workshop
Utilizing Supporting Evidence to Improve Dynamic Requirements Traceability
RE '05 Proceedings of the 13th IEEE International Conference on Requirements Engineering
ACM Transactions on Software Engineering and Methodology (TOSEM)
Electronic Notes in Theoretical Computer Science (ENTCS)
Linking e-mails and source code artifacts
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Mining textual requirements to assist architectural software design: a state of the art review
Artificial Intelligence Review
Hi-index | 0.00 |
Tracking a variety of traceability links between artifacts assists software developers in comprehension, efficient development, and effective management of a system. Traceability systems to date based on various Information Retrieval (IR) techniques have been faced with a major open research challenge: how to extract these links with both high precision and high recall. In this paper we describe an experimental approach that combines Regular Expression, Key Phrases, and Clustering with IR techniques to enhance the performance of IR for traceability link recovery between documents and source code. Our preliminary experimental results show that our combination technique improves the performance of IR, increases the precision of retrieved links, and recovers more true links than IR alone.