Data flow analysis across tuplespace process boundaries

A current limitation of compilers for shared memory parallel languages is their restricted use of traditional code-improving transformations, such as constant propagation and dead code elimination. A major problem lies in the lack of data flow analysis techniques for programs with user-specified parallelism. The authors demonstrate how data flow analysis remains quite viable in a compiler for shared memory parallel programs in a structured distributed shared memory environment, in which a shared space of tuples is accessed by properly synchronized methods. They demonstrate standard intraprocess data flow analysis performed in the midst of tuplespace communication statements, and present improvements to the precision of the analysis in the presence of these statements. They present a data flow system to compute reaching definitions across process boundaries, and a technique to improve the precision of this interprocess analysis. Lastly, some transformations enabled by this analysis are presented