Abstract
This introductory paper has been written for readers who know nothing about model checking but do know about software. Its aim is to present, almost without mathematical terms, the fundamental general approaches on which the papers in this Special Section build, and give an idea of what kind of contribution each paper makes. The main issues discussed are motivation for model checking, state spaces, and bounded model checking with sat solvers. Individual papers lead to discuss the following ideas: exploiting a distributed computing environment for model checking, constructing those states first that look most promising for eventually finding errors, only constructing a representative subset of states, the representation of contents of variables in an abstract way with approximation from below, and the use of more general solvers than sat solvers in bounded model checking.
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