Efficiently generating test vectors with state pruning
Ying Chen, Dennis Abts, David J. Lilja · 2005
This paper extends the depth first search (DFS) used in the previously proposed witness string method for generating efficient test vectors. A state pruning method is added that exploits different search heuristics in simultaneous searches. Using an IBM Power4 multiprocessor system with the Berkeley Active Message library, we show that this new method of state pruning is efficient and produces quantitatively better witness strings compared to both pure and guided DFS.