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Conference Papers Year : 2019

A Multiple Fault Localization Approach based on Multicriteria Analytical Hierarchy Process

Abstract

Fault localization problem is one of the most difficult processes in software debugging. Several spectrum-based ranking metrics have been proposed and none is shown to be empirically optimal. In this paper, we consider the fault localization problem as a multicriteria decision making problem. The proposed approach tackles the different metrics by aggregating them into a single metric using a weighted linear formulation. A learning step is used to maintain the right expected weights of criteria. This approach is based on Analytic Hierarchy Process (AHP), where a ranking is given to a statement in terms of suspiciousness according to a comparison of ranks given by the different metrics. Experiments performed on standard benchmark programs show that our approach enables to propose a more precise localization than existing spectrum-based metrics.
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Dates and versions

lirmm-02089746 , version 1 (04-04-2019)

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Noureddine Aribi, Nadjib Lazaar, Yahia Lebbah, Samir Loudni, Mehdi Maamar. A Multiple Fault Localization Approach based on Multicriteria Analytical Hierarchy Process. AITest 2019 - 1st IEEE International Conference on Artificial Intelligence Testing, Apr 2019, San Francisco, United States. pp.1-8, ⟨10.1109/AITest.2019.00-16⟩. ⟨lirmm-02089746⟩
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