Sharing analysis of arrays, collections, and recursive structures

Precise modeling of the program heap is fundamental for under-standing the behavior of a program, and is thus of signiflcant in-terest for many optimization applications. One of the fundamental properties of the heap that can be used in a range of optimization techniques is the sharing relationships between the elements in an array or collection. If an analysis can determine that the memory locations pointed to by different entries of an array (or collection) are disjoint, then in many cases loops that traverse the array can be vectorized or transformed into a thread-parallel versión. This paper introduces several novel sharing properties over the concrete heap and corresponding abstractions to represent them. In conjunction with an existing shape analysis technique, these abstractions allow us to precisely resolve the sharing relations in a wide range of heap structures (arrays, collections, recursive data structures, composite heap structures) in a computationally efflcient manner. The effec-tiveness of the approach is evaluated on a set of challenge problems from the JOlden and SPECjvm98 suites. Sharing information ob-tained from the analysis is used to achieve substantial thread-level parallel speedups