Feature Location using Probabilistic Ranking of Methods based on Execution Scenarios and Information Retrieval. Poshyvanyk, D., Gu�h�neuc, Y., Marcus, A., Antoniol, G., & Rajlich, V. Transactions on Software Engineering (TSE), 33(6):420–432, IEEE CS Press, June, 2007. 14 pages.
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Paper abstract bibtex
Paper abstract bibtex This paper recasts the problem of feature location in source code as a decision-making problem in the presence of uncertainty. The solution to the problem is formulated as a combination of expert opinions. The experts in this case are represented by two existing techniques for feature location: Scenario-based Probabilistic Ranking of events and an Information Retrieval-based technique that uses Latent Semantic Indexing. The combination of these two methods is empirically evaluated through several case studies. The case studies use the source code of the Mozilla web browser and the Eclipse integrated development environment. The results show that the combined technique significantly improves the effectiveness of feature location when compared to each of the techniques used independently.
@ARTICLE{Poshyvanyk07-TSE-Promesir,
AUTHOR = {Denys Poshyvanyk and Yann-Ga�l Gu�h�neuc and
Andrian Marcus and Giuliano Antoniol and V�clav Rajlich},
JOURNAL = {Transactions on Software Engineering (TSE)},
TITLE = {Feature Location using Probabilistic Ranking of Methods
based on Execution Scenarios and Information Retrieval},
YEAR = {2007},
MONTH = {June},
NOTE = {14 pages.},
NUMBER = {6},
PAGES = {420--432},
VOLUME = {33},
EDITOR = {Jeff Kramer},
KEYWORDS = {Topic: <b>Requirements and features</b>,
Venue: <b>TSE</b>},
PUBLISHER = {IEEE CS Press},
URL = {http://www.ptidej.net/publications/documents/TSE07.doc.pdf},
ABSTRACT = {This paper recasts the problem of feature location in
source code as a decision-making problem in the presence of
uncertainty. The solution to the problem is formulated as a
combination of expert opinions. The experts in this case are
represented by two existing techniques for feature location:
Scenario-based Probabilistic Ranking of events and an Information
Retrieval-based technique that uses Latent Semantic Indexing. The
combination of these two methods is empirically evaluated through
several case studies. The case studies use the source code of the
Mozilla web browser and the Eclipse integrated development
environment. The results show that the combined technique
significantly improves the effectiveness of feature location when
compared to each of the techniques used independently.}
}Downloads: 0
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The solution to the problem is formulated as a combination of expert opinions. The experts in this case are represented by two existing techniques for feature location: Scenario-based Probabilistic Ranking of events and an Information Retrieval-based technique that uses Latent Semantic Indexing. The combination of these two methods is empirically evaluated through several case studies. The case studies use the source code of the Mozilla web browser and the Eclipse integrated development environment. 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