Abstract. We study two natural models of randomly generated constraint satisfaction problems. We determine how quickly the domain size must grow with n to ensure that these models ...
Abstract. We extend the common depth-first backtrack search for constraint satisfaction problems with randomized variable and value selection. The resulting methods are applied to ...
Path-oriented Random Testing (PRT) aims at generating a uniformly spread out sequence of random test data that activate a single control flow path within an imperative program. T...
We present a novel algorithm for test data generation that is based on techniques used in formal software verification. Prominent examples of such formal techniques are symbolic ex...
We present the results of an empirical study of several constraint satisfaction search algorithms and heuristics. Using a random problem generator that allows us to create instanc...