Heap Abstraction Beyond Context-Freeness.

The aim of shape analysis is to discover precise abstractions of the reachable data structures in a programu0027s heap. This paper develops a shape analysis for reasoning about relational properties of data structures, such as balancedness of trees or lengths of lists. Both the concrete and the abstract domain are represented by hypergraphs. The analysis is based on user-defined indexed graph grammars to guide concretization and abstraction. This novel extension of context-free graph grammars is powerful enough to model complex data structures, such as balanced binary trees with parent pointers, while preserving most desirable properties of context-free graph grammars. One strength of our analysis is that no artifacts apart from grammars are required from the user; it thus offers a high degree of automation. In particular, indexed graph grammars naturally describe how a data structure evolves and require no deep knowledge about relational properties. We have implemented a prototype of our analysis and report on first experimental results.