An ML-style Record Calculus with Extensible Records
| Autor: | Alves, Sandra, Ramos, Miguel |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | EPTCS 351, 2021, pp. 1-17 |
| Druh dokumentu: | Working Paper |
| DOI: | 10.4204/EPTCS.351.1 |
| Popis: | In this work, we develop a polymorphic record calculus with extensible records. Extensible records are records that can have new fields added to them, or preexisting fields removed from them. We also develop a static type system for this calculus and a sound and complete type inference algorithm. Most ML-style polymorphic record calculi that support extensible records are based on row variables. We present an alternative construction based on the polymorphic record calculus developed by Ohori. Ohori based his polymorphic record calculus on the idea of kind restrictions. This allowed him to express polymorphic operations on records such as field selection and modification. With the addition of extensible types, we were able to extend Ohori's original calculus with other powerful operations on records such as field addition and removal. Comment: In Proceedings MFPS 2021, arXiv:2112.13746 |
| Databáze: | arXiv |
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