Testing Your (Static Analysis) Truths.

LOPSTR(2020)

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摘要
Static analysis is nowadays an essential component of many software development toolsets. Despite some notorious successes in the validation of compilers, comparatively little work exists on the systematic validation of static analyzers, whose correctness and reliability is critical if they are to be inserted in production environments. Contributing factors may be the intrinsic difficulty of formally verifying code that is quite complex and of finding suitable oracles for testing it. In this paper, we propose a simple, automatic method for testing abstract interpretation-based static analyzers. Broadly, it consists in checking, over a suite of benchmarks, that the properties inferred statically are satisfied dynamically. The main advantage of our approach is its simplicity, which stems directly from framing it within the Ciao assertion-based validation framework, and its blended static/dynamic assertion checking approach. We show that in this setting, the analysis can be tested with little effort by combining the following components already present in the framework: the static analyzer , the assertion run-time checking mechanism, the random test case generator , and the unit-test framework . Together they compose a tool that can effectively discover and locate errors in the different components of the analysis framework. We apply our approach to test some of CiaoPP’s analysis domains over a wide range of programs, successfully finding non-trivial, previously undetected bugs, with a low degree of effort.
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关键词
Static analysis, Run-time checks, Random testing, Assertions, Abstract interpretation, Program analysis, (Constraint) logic programming
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