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By Dennis Dams (auth.), Dragan Bošnački, Stefan Edelkamp (eds.)
This booklet constitutes the refereed complaints of the 14th foreign SPIN workshop on version Checking software program, SPIN 2007, held in Berlin, Germany in July 2007 along side the nineteenth overseas convention on desktop Aided Verification, CAV 2007.
The 14 revised complete papers awarded including four software presentation papers and the abstracts of two invited talks have been conscientiously reviewed and chosen from 39 submissions. The papers are prepared in topical sections on directed version checking, partial order relief, application research, exploration advances, modeling and case stories, in addition to instrument demonstrations.
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The description is given in Algorithm 1. Note that, once the distances are computed by a BFS, a backward search in the graph starting from s and following edges for which the distance decreases until r (hence distance 0) is reached, allows to construct efficiently the shortest path from r to s. Unfortunately, backward searches cannot be used in practice 28 P. Gastin and P. Moro Algorithm 1. pop(); with SPIN since it would be hard to compute the set of predecessors of a state. , if the state is reached by an assignment to some integer variable.
More precisely, for each state we store an integer (depth field) and a few bits (bfs flag or marked). In fact, these flags should be erased after each call to an algorithm, this is omitted for simplicity. The size of each queue is at most linear in the number of states. 4 Improvements The first improvement is to use, before calling Algorithm 5, a nested-DFS algorithm such as [CVWY92, HPY96, SE05, GMZ04], or a Tarjan-like algorithm [Cou99, VG04]2 . This allows to perform a linear time search to detect whether there exists some counterexample, and in this case it can also initialize maxdepth to the size of the counterexample found in order to speed-up Algorithm 5.
205–219. : Reliable hashing without collosion detection. In: Courcoubetis, C. ) CAV 1993. LNCS, vol. 697, pp. 59–70. Springer, Heidelberg (1993) Generating Counter-Examples Through Randomized Guided Search Neha Rungta and Eric G. Mercer Department of Computer Science Brigham Young University Provo, UT 84602, USA Abstract. Computational resources are increasing rapidly with the explosion of multi-core processors readily available from major vendors. Model checking needs to harness these resources to help make it more effective in practical verification.