Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval

Author

Poshyvanyk, Denys ; Guéhéneuc, Yann-Gaël ; Marcus, Andrian ; Antoniol, Giuliano ; Rajlich, Vá Clav

Author_Institution

Dept. of Comput. Sci., Wayne State Univ., Detroit, MI

Volume

33

Issue

6

fYear

2007

fDate

6/1/2007 12:00:00 AM

Firstpage

420

Lastpage

432

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 the opinions of different experts. The experts in this work are two existing techniques for feature location: a scenario-based probabilistic ranking of events and an information-retrieval-based technique that uses latent semantic indexing. The combination of these two experts is empirically evaluated through several case studies, which use the source code of the Mozilla Web browser and the Eclipse integrated development environment. The results show that the combination of experts significantly improves the effectiveness of feature location as compared to each of the experts used independently

Keywords

decision making; information retrieval; probability; program diagnostics; Eclipse integrated development; Mozilla Web browser; decision-making problem; feature location; information retrieval; latent semantic indexing; scenario-based probabilistic event ranking; Computer Society; Computer bugs; Decision making; Indexing; Information analysis; Information retrieval; Open source software; Performance analysis; Programming profession; Uncertainty; Latent Semantic Indexing; Program understanding; concept location; dynamic and static analyses; feature identification; information retrieval; open source software.; scenario-based probabilistic ranking;

fLanguage

English

Journal_Title

Software Engineering, IEEE Transactions on

Publisher

ieee

ISSN

0098-5589

Type

jour

DOI

10.1109/TSE.2007.1016

Filename

4181710