Incremental False Path Elimination for Static Software Analysis

Abstract. In this work we introduce a novel approach for removing false positives in static program analysis. We present an incremental algorithm that investigates paths to failure locations with respect to fea-sibility. The feasibility test it done by interval constraint solving over a semantic abstraction of program paths. Sets of infeasible paths can be ruled out by enriching the analysis incrementally with observers. Much like counterexample guided abstraction refinement for software verifica-tion our approach enables to start static program analysis with a coarse syntactic abstraction and use richer semantic information to rule out false positives when necessary and possible. Moreover, we present our implementation in the Goanna static analyzer and compare it to other tools for C/C++ program analysis.