Affiliation:
1. IBM T. J. Watson Research Center, Yorktown Heights, NY
Abstract
We reformulate interval analysis so that it can he applied to any monotone data-flow problem, including the nonfast problems of flow-insensitive interprocedural analysis. We then develop an incremental interval analysis technique that can be applied to the same class of problems. When applied to flow-insensitive interprocedural data-flow problems, the resulting algorithms are simple, practical, and efficient. With a single update, the incremental algorithm can accommodate any sequence of program changes that does not alter the structure of the program call graph. It can also accommodate a large class of structural changes. For alias analysis, we develop an incremental algorithm that obtains the exact solution as computed by an exhaustive algorithm. Finally, we develop a transitive closure algorithm that is particularly well suited to the very sparse matrices associated with the problems we address.
Publisher
Association for Computing Machinery (ACM)
Cited by
69 articles.
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