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When a program is not conform to its specification, i.e., the program is erroneous, provide useful information for error localization is an important task to debug the program but complex at the same time. The goal is to provide a reduced set of suspicious statements to understand the origin of errors in the program. In our research we propose a new constraint-based approach to support the problem of error localization for which a counterexample is available, i.e., a test case proving the non conformity. From the counterexample, our approach generate a constraint system for each path of the CFG (Control Flow Graph) for which at most k conditional statements are suspected. Then, we calculate Minimal Correction Subsets (MCS) of bounded size for each erroneous path. The removal of one of these sets of constraints yields a Maximal Satisfiable Subset (MSS), a maximal subset of constraints satisfying the postcondition. We export and adapt the generic algorithm proposed by Liffiton and Sakallah to handle programs with numerical statements more efficiently. We present preliminary experimental results that are quite encouraging.