Generics for the working ML'er

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Generics for the working ML'er

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International Conference on Functional Programming archive
Proceedings of the 2007 workshop on Workshop on ML table of contents

Freiburg, Germany

SESSION: Session 3 table of contents

Pages: 71 - 82

Year of Publication: 2007

ISBN:978-1-59593-676-9

Author

Vesa A.J. Karvonen

University of Helsinki, Helsinki, Finland

Sponsors

ACM: Association for Computing Machinery
SIGPLAN: ACM Special Interest Group on Programming Languages

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 4, Downloads (12 Months): 29, Citation Count: 1

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ABSTRACT

Generic values are type-indexed values defined over the structure of types. A popular and pragmatic approach to type-indexed values in ML-like languages is to use a value-dependent encoding,where the type representations carry the values being indexed. Unfortunately, the approach has a major drawback. Because the resulting encoding is specific to a particular set of values, extending an encoding with new values requires modifying it.In this paper, we discuss an approach to generics based on the value-dependent encoding approach. We extend upon previous work inseveral ways. We present a technique that allows an existing value-dependent encoding to be extended with new values. We show how toencode type representations over essentially all the ML-types. We also show how to compute fixed points over arbitrary products. Our techniques have been implemented in Standard ML, do not compromise abstraction, and require only a fixed number of combinators.

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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