Selective conjunction of context-sensitivity and octagon domain toward scalable and precise global static analysis

Abstract

We present a practical technique for achieving a scalable and precise global static analysis by selectively applying context-sensitivity and the octagon relational domain. For precise analysis, context-sensitivity and relational analysis are key properties, but it has been hard to practically combine both of them. Our approach turns on those precision improvement features only when the analysis is likely to improve the precision to resolve given queries. The guidance comes from an impact pre-analysis that estimates the impact of a fully context-sensitive and relational octagon analysis. We designed a cost-effective pre-analysis and implemented this method in a realistic octagon analysis for full C. The experimental results show that our approach proves eight times more queries, while saving the time cost by 73.1% compared with a partially relational octagon analysis enabled by a syntactic heuristic. Copyright (C) 2017 John Wiley & Sons, Ltd.