Software model checkers can be used to generate high-quality test cases from counterexamples of a reachability analysis. However, naïvely invoking a software model checker for each test goal in isolation does not scale to large programs as a repeated construction of an abstract program model is expensive. In contrast, invoking a software model checker for reaching all test goals in a single run leads to few abstraction possibilities and thus to low scalability. Therefore, our approach pursues a test-suite generation technique that incorporates configurable multi-goal set partitioning (MGP) including configurable partitioning strategies and simultaneous processing of multiple test goals in one reachability analysis. Our approach employs recent techniques from multi-property verification in order to control the computational overhead for tracking multi-goal reachability information. Our tool, called CPA/Tiger-MGP, uses predicate-abstraction-based program analysis in the modelchecking framework CPAchecker.
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