Automatically Inferring Sound Dataflow Functions from Dataflow Fact Schemas

COCV 2005, Edinburgh, UK, April 3, 2005
Erika Rice, Sorin Lerner, and Craig Chambers
In previous work, we presented a language called Rhodium for writing program analyses and transformations that could be checked for soundness automatically. In this work, we present an algorithm for automatically inferring sound flow func- tions given only a set of dataflow fact schemas. By generating the flow functions mechanically, our approach reduces the burden on compiler writers. This paper presents a detailed description of our algorithm and shows how it works on several examples. We have run our algorithm by hand on all the statements of a simple C-like intermediate language for an is-constant fact schema, a points-to fact schema, and a variable-equality fact schema. Our algorithm generated a total of 71 rules for these cases. It generated all but one of the rules we had written by hand for these dataflow fact schemas, and it also generated new useful rules that we had not thought of previously.

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