Cause clue clauses: error localization using maximum satisfiability

Abstract

Much effort is spent by programmers everyday in trying to reduce long, failing execution traces to the cause of the error. We present an algorithm for error cause localization based on a reduction to the maximal satisfiability problem (MAX-SAT), which asks what is the maximum number of clauses of a Boolean formula that can be simultaneously satisfied by an assignment. At an intuitive level, our algorithm takes as input a program and a failing test, and comprises the following three steps. First, using bounded model checking, and a bound obtained from the execution of the test, we encode the semantics of a bounded unrolling of the program as a Boolean trace formula. Second, for a failing program execution (e.g., one that violates an assertion or a post-condition), we construct an unsatisfiable formula by taking the formula and additionally asserting that the input is the failing test and that the assertion condition does hold at the end. Third, using MAX-SAT, we find a maximal set of clauses in this formula that can be satisfied together, and output the complement set as a potential cause of the error.