This paper presents a generic method which uses the framework of Abstract Interpretation as defined by the Cousots [6] to build type reconstruction algorithms. Fundamentally, this method is based upon the combination of an upper and a lower approximation as well as the use of widening operators to insure algorithm termination. We illustrate this method with a type reconstruction algorithm of the expressions of a ML-like language more or less similar to Mycroft’s ML+ type system[14]. We first show that restricting recursively defined constants to monomorphic types—as in ML—can be seen as a widening operator. Then we exhibit a less restrictive operator which lets recursively defined expressions have polymorphic types, while still insuring algorithm termination.
CITATION STYLE
Monsuez, B. (1992). Polymorphic typing by abstract interpretation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 652 LNCS, pp. 217–228). Springer Verlag. https://doi.org/10.1007/3-540-56287-7_107
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