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Automatic inference of optimizer flow functions from semantic meanings
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Conference on Programming Language Design and Implementation archive
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation table of contents
San Diego, California, USA
SESSION: Programs analyzed table of contents
Pages: 135 - 145  
Year of Publication: 2007
ISBN:978-1-59593-633-2
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Authors
Erika Rice Scherpelz  Google, Kirkland, WA
Sorin Lerner  University of California, San Diego, San Diego, CA
Craig Chambers  University of Washington, Seattle, WA
Sponsors
SIGPLAN: ACM Special Interest Group on Programming Languages
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Previous work presented a language called Rhodium for writing program analyses and transformations, in the form of declarative flow functions that propagate instances of user-defined dataflow fact schemas. Each dataflow fact schema specifies a semantic meaning, which allows the Rhodium system to automatically verify the correctness of the user's flow functions. In this work, we have reversed the roles of the flow functions and semantic meanings: rather than checking the correctness of the user-written flow functions using the facts' semantic meanings, we automatically infer correct flow functions solely from the meanings of the dataflow fact schemas. We have implemented our algorithm for inferring flow functions from fact schemas in the context of the Whirlwind compiler, and have used this implementation to infer flow functions for a variety of fact schemas. The automatically generated flow functions cover most of the situations covered by an earlier suite of handwritten rules.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Erika Rice Scherpelz: colleagues
Sorin Lerner: colleagues
Craig Chambers: colleagues