Shape Analysis for Unstructured Sharing
SAS 2015: International Static Analysis Symposium


Shape analysis aims to infer precise structural properties of imperative memory states and has been applied heavily to verify safety properties on imperative code over pointer-based data structures. Recent advances in shape analysis based on separation logic has leveraged summarization predicates that describe unbounded heap regions like lists or trees using inductive definitions. Unfortunately, data structures with unstructured sharing, such as graphs, are challenging to describe and reason about in such frameworks. In particular, when the sharing is unstructured, it cannot be described inductively in a local manner. In this paper, we propose a global abstraction of sharing based on set-valued variables that when integrated with inductive definitions enables the specification and shape analysis of structures with unstructured sharing.


@string{SAS = "International Static Analysis Symposium (SAS)"}
  author = {Huisong Li and Bor-Yuh Evan Chang and Xavier Rival},
  title = {Shape Analysis for Unstructured Sharing},
  booktitle = SAS,
  year = {2015},
  pages = {90-108},