Publication Type

Conference Proceeding Article

Publication Date

11-2011

Abstract

Many spectrum-based fault localization measures have been proposed in the literature. However, no single fault localization measure completely outperforms others: a measure which is more accurate in localizing some bugs in some programs is less accurate in localizing other bugs in other programs. This paper proposes to compose existing spectrum-based fault localization measures into an improved measure. We model the composition of various measures as an optimization problem and present a search-based approach to explore the space of many possible compositions and output a heuristically near optimal composite measure. We employ two search-based strategies including genetic algorithm and simulated annealing to look for optimal solutions and compare the effectiveness of the resulting composite measures on benchmark software systems. Compared to individual spectrum-based fault localization techniques, our composite measures perform statistically significantly better.

Discipline

Software Engineering

Research Areas

Software Systems

Publication

ASE 2011: 26th IEEE/ACM International Conference on Automated Software Engineering, 6-10 November 2011, Lawrence, KS: Proceedings

First Page

556

Last Page

559

ISBN

9781457716386

Identifier

10.1109/ASE.2011.6100124

Publisher

IEEE

City or Country

Lawrence, USA

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.1109/ASE.2011.6100124

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