A dataflow analysis to improve SAT-based bounded program verification
SEFM'11 Proceedings of the 9th international conference on Software engineering and formal methods
Parallel bounded analysis in code with rich invariants by refinement of field bounds
Proceedings of the 2013 International Symposium on Software Testing and Analysis
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We present a novel approach to optimize incremental scope-bounded checking of programs using a relational constraint solver. Given a program and its correctness specification, scope-bounded checking encodes control-flow and data-flow of bounded code segments into declarative formulas and uses constraint solvers to search for correctness violations. For non-trivial programs, the formulas are often complex and represent a heavy workload that can choke the solvers. To scale scope-bounded checking, our previous work introduced an incremental approach that uses the program’s control-flow as a basis of partitioning the program and generating several sub-formulas, which represent simpler problem instances for the underlying solvers. This paper introduces a new approach that uses the program’s dataflow, specifically variable-definitions, as a basis for incremental checking. Experimental results show that the use of data-flow provides a significant reduction in the number of variables in the encoded formulas over the previous control-flow-based approach, thereby further improving scalability of scopebounded checking.