Poster: Accelerating Counterexample Detection in Software Model Checking

In CEGAR based counterexample detecting, the challenge is loops in programs since the computation and data related to loops can have statically unknown bounds. This paper devotes to speeding up counterexample detection in CEGAR based software model checking by summarizing simple loops. Specifically, for simple loops, instead of unwinding it for a large number of times, a novel approach by summarizing is given to analyze the program in a not only fast but also accurate way. With this approach, we always assume that the loop body has been iterated for n, n <; 0, times; and after the n execution of the loop body, the loop condition will not be satisfied. As a result, a linear equation which can be easily solved by an SMT solver is formalized directly.