A framework for determining useful parallelism
Frances Allen, Michael Burke, et al.
ICS 1988
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. © 1990, ACM. All rights reserved.
Frances Allen, Michael Burke, et al.
ICS 1988
Michael Hind, Michael Burke, et al.
Scientific Programming
Frances Allen, Michael Burke, et al.
Journal of Parallel and Distributed Computing
Rajesh Bordawekar, Michael Burke, et al.
OOPSLA 2005