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Hob is a program analysis system that enables the focused application of multiple analyses to different modules in the same program. In our approach, each module encapsulates one or more data structures and uses membership in abstract sets to characterize how objects participate in data structures. Each analysis verifies that the implementation of the module 1) preserves important internal data structure consistency properties and 2) correctly implements a set algebra interface that characterizes the effects of operations on the data structure. Collectively, the analyses use the set algebra to 1) characterize how objects participate in multiple data structures and to 2) enable the interanalysis communication required to verify properties that depend on multiple modules analyzed by different analyses. We implemented our system and deployed several pluggable analyses, including a flag analysis plug--in for modules in which abstract set membership is determined by a flag field in each object, a PALE shape analysis plug-in, and a theorem proving plug-in for analyzing arbitrarily complicated data structures. Our experience shows that our system can effectively 1) verify the consistency of data structures encapsulated within a single module and 2) combine analysis results from different analysis plug-ins to verify properties involving objects shared by multiple modules analyzed by different analyses.
Typestate, data structure, invariant, program analysis, program verification, shape analysis, formal methods, programming language design.
Viktor Kuncak, Martin C. Rinard, Patrick Lam, Karen Zee, "Modular Pluggable Analyses for Data Structure Consistency", IEEE Transactions on Software Engineering, vol. 32, no. , pp. 988-1005, December 2006, doi:10.1109/TSE.2006.125
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