Data Structure Analysis: An Efficient Context-Sensitive Heap Analysis

This paper presents an efficient context-sensitive heap analysis algorithm called Data Structure Analysis designed to enable analyses and transformations on entire disjoint recursive data structures. The analysis has several challenging properties needed to enable such transformations: context-sensitivity with cloning (essential for proving disjointness), field-sensitivity, and the use of an explicit heap model rather than just alias information. It is also applicable to arbitrary C programs. To our knowledge no prior work provides all these properties and is efficient and scalable enough for large programs. Measurements for 29 programs show that the algorithm is extremely fast, space-efficient, and scales almost linearly across 3 orders-of-magnitude of code size.