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Conference papers

Shape Analysis for Unstructured Sharing

Abstract : 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 sum-marization predicates that describe unbounded heap regions like lists or trees using inductive definitions. Unfortunately, data structures with un-structured 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.
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Huisong Li, Xavier Rival, Bor-yuh Evan Chang. Shape Analysis for Unstructured Sharing. SAS 2015 - 22nd International Symposium on Static Analysis, Sep 2015, Saint-Malo, France. pp.90-108, ⟨10.1007/978-3-662-48288-9_6⟩. ⟨hal-01249418⟩

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