Abstract
We present a novel approach to optimize scope-bounded checking programs using a relational constraint solver. Given a program and its correctness specification, the traditional approach translates a bounded code segment of the entire program into a declarative formula and uses a constraint solver to search for any correctness violations. Scalability is a key issue with such approaches since for non-trivial programs the formulas are complex and represent a heavy workload that can choke the solvers. Our insight is that bounded code segments, which can be viewed as a set of (possible) execution paths, naturally lend to incremental checking through a partitioning of the set, where each partition represents a sub-set of paths. The partitions can be checked independently, and thus the problem of scope-bounded checking for the given program reduces to several sub-problems, where each sub-problem requires the constraint solver to check a less complex formula, thereby likely reducing the solver’s overall workload. Experimental results show that our approach provides significant speed-ups over the traditional approach.
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Shao, D., Khurshid, S., Perry, D.E. (2009). An Incremental Approach to Scope-Bounded Checking Using a Lightweight Formal Method. In: Cavalcanti, A., Dams, D.R. (eds) FM 2009: Formal Methods. FM 2009. Lecture Notes in Computer Science, vol 5850. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05089-3_48
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DOI: https://doi.org/10.1007/978-3-642-05089-3_48
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