Existential Label Flow Inference via CFL Reachability

Polyvios Pratikakis (University of Maryland), Jeffrey S. Foster (University of Maryland) and Michael Hicks (University of Maryland)


In programming languages, existential quantification is useful for describing relationships among members of a structured type. For example, we may have a list in which there exists some mutual exclusion lock l in each list element such that l protects the data stored in that element. With this information, a static analysis can reason about the relationship between locks and locations in the list even when the precise identity of the lock and/or location is unknown. To facilitate the construction of such static analyses, this paper presents a context-sensitive label flow analysis algorithm with support for existential quantification. Label flow analysis is a core part of many static analysis systems. Following Rehof et al, we use context-free language (CFL) reachability to develop an efficient O(n^3) label flow inference algorithm. We prove the algorithm sound by reducing its derivations to those in a system based on polymorphically-constrained types, in the style of Mossin. We have implemented a variant our analysis as part of a data race detection tool for C programs.