Abstract
Data flow analysis is a technique essential to the compile-time optimization of computer programs, wherein facts relevant to program optimizations are discovered by the global propagation of facts obvious locally. This paper extends several known techniques for data flow analysis of sequential programs to the static analysis of distributed communicating processes. In particular, we present iterative algorithms for detecting unreachable program statements, and for determining the values of program expressions. The latter information can be used to place bounds on the size of variables and messages. Our main innovation is theevent spanning graph, which serves as a heuristic for ordering the nodes through which data flow information is propagated. We consider bothstatic communication, where all channel arguments are constants, and the more difficultdynamic communication, where channel arguments may be variables and channels may be passed as messages.
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A preliminary version of this paper appeared in the proceedings of the Sixth Annual ACM Symposium on Principles of Programming Languages, pp. 257–268, June 1979.
Supported by National Science Foundation Grant NSF MCS82-00269 and the Office of Naval Research Contract N00014-80-C-0647.
Supported by National Science Foundation Grants NSF DCR-8505873 and NSF CCR-8704309.
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Reif, J.H., Smolka, S.A. Data flow analysis of distributed communicating processes. Int J Parallel Prog 19, 1–30 (1990). https://doi.org/10.1007/BF01407862
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DOI: https://doi.org/10.1007/BF01407862