Type-based parametric analysis of program families
Sheng Chen, Martin Erwig · 2014
Previous research on static analysis for program families has focused on lifting analyses for single, plain programs to program families by employing idiosyncratic representations. The lifting effort typically involves a significant amount of work for proving the correctness of the lifted algorithm and demonstrating its scalability. In this paper, we propose a parameterized static analysis framework for program families that can automatically lift a class of type-based static analyses for plain programs to program families. The framework consists of a parametric logical specification and a parametric variational constraint solver. We prove that a lifted algorithm is correct provided that the underlying analysis algorithm is correct. An evaluation of our framework has revealed an error in a previous manually lifted analysis. Moreover, performance tests indicate that the overhead incurred by the general framework is bounded by a factor of 2.