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Projective ML
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Source Conference on LISP and Functional Programming archive
Proceedings of the 1992 ACM conference on LISP and functional programming table of contents
San Francisco, California, United States
Pages: 66 - 75  
Year of Publication: 1992
ISBN:0-89791-481-3
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SIGPLAN: ACM Special Interest Group on Programming Languages
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
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ACM  New York, NY, USA
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Downloads (6 Weeks): 8,   Downloads (12 Months): 26,   Citation Count: 7
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ABSTRACT

We propose a projective lambda calculus as the basis for operations on records. Projections operate on elevations, that is, records with defaults. This calculus extends lambda calculus while keeping its essential properties. We build projective ML from this calculus by adding the ML Let typing rule to the simply typed projective calculus. We show that projective ML possesses the subject reduction property, which means that well-typed programs can be reduced safely. Elevations are practical data structures that can be compiled efficiently. Moreover, standard records are difinable in terms of projections.


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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