Fault localization using itemset mining under constraints - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Journal Articles Automated Software Engineering Year : 2017

Fault localization using itemset mining under constraints

Abstract

We introduce in this paper an itemset mining approach to tackle the fault localization problem, which is one of the most difficult processes in software debug- ging. We formalize the problem of fault localization as finding the k best patterns satisfying a set of constraints modelling the most suspicious statements. We use a Constraint Programming (CP) approach to model and to solve our itemset based fault localization problem. Our approach consists of two steps: (i) mining top-k suspicious suites of statements; (ii) fault localization by processing top-k patterns. Experiments performed on standard benchmark programs show that our approach enables to pro- pose a more precise localization than a standard approach
Fichier principal
Vignette du fichier
cfm-ase15.pdf (591.31 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

lirmm-01276633 , version 1 (17-10-2018)

Identifiers

Cite

Mehdi Maamar, Nadjib Lazaar, Samir Loudni, Yahia Lebbah. Fault localization using itemset mining under constraints. Automated Software Engineering, 2017, 24 (2), pp.341-368. ⟨10.1007/s10515-015-0189-z⟩. ⟨lirmm-01276633⟩
339 View
273 Download

Altmetric

Share

Gmail Facebook X LinkedIn More