Une approche CSP pour l'aide à la localisation d'erreurs
This work addresses error localization in software debugging, but it appears incremental as it builds on existing algorithms and focuses on specific program types.
The paper tackles the problem of locating errors in programs by introducing a new constraint satisfaction problem (CSP) approach that generates minimal correction sets for paths with at most k erroneous conditional statements, using an extended algorithm to handle numerical statements more efficiently, with preliminary experimental results described as encouraging.
We introduce in this paper a new CP-based approach to support errors location in a program for which a counter-example is available, i.e. an instantiation of the input variables that violates the post-condition. To provide helpful information for error location, we generate a constraint system for the paths of the CFG (Control Flow Graph) for which at most k conditional statements may be erroneous. Then, we calculate Minimal Correction Sets (MCS) of bounded size for each of these paths. The removal of one of these sets of constraints yields a maximal satisfiable subset, in other words, a maximal subset of constraints satisfying the post condition. We extend the algorithm proposed by Liffiton and Sakallah \cite{LiS08} to handle programs with numerical statements more efficiently. We present preliminary experimental results that are quite encouraging.