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There is an intimate link between program structure and behaviour. Exploiting this link to phrase program correctness problems in terms of the structural properties of a program graph rather than in terms of its unfoldings is a useful strategy for making analyses more tractable. This paper presents a characterisation of behavioural program properties through sets of structural properties by means of a translation. The characterisation is given in the context of a program model based on control flow graphs of sequential programs with possibly recursive procedures, and properties expressed in a fragment of the modal \mu-calculus with boxes and greatest fixed-points only. The property translation is based on a tableau construction that conceptually amounts to symbolic execution of the behavioural formula, collecting structural constraints along the way. By keeping track of the subformulae that have been examined, recursion in the structural constraints can be identified and captured by fixed-point formulae. The tableau construction terminates, and the characterisation is exact, i.e., the translation is sound and complete. A prototype implementation has been developed. We discuss several applications of the characterisation, in particular compositional verification for behavioural properties, based on maximal models.

We present a new approach to program testing which enables the programmer to specify test suites in terms of a versatile query language. Our query language subsumes standard coverage criteria ranging from simple basic block coverage all the way to predicate complete coverage and multiple condition coverage, but also facilitates on-the-fly requests for test suites specific to the code structure, to external requirements, or to ad hoc needs arising in program understanding/exploration. The query language is supported by a model checking backend which employs the CBMC framework. Our main algorithmic contribution is a method called iterative constraint strengthening which enables us to solve a query for an arbitrary coverage criterion by a single call to the model checker and a novel form of incremental SAT solving: Whenever the SAT solver finds a solution, our algorithm compares this solution against the coverage criterion, and strengthens the clause database with additional clauses which exclude redundant new solutions. We demonstrate the scalability of our approach and its ability to compute compact test suites with experiments involving device drivers, automotive controllers, and open source projects. © 2009 Springer Berlin Heidelberg.