Kind Inference for the FreeST Programming Language

Autor:	Almeida, Bernardo, Mordido, Andreia, Vasconcelos, Vasco T.
Rok vydání:	2023
Předmět:	Computer Science - Programming Languages Computer Science - Software Engineering
Zdroj:	EPTCS 378, 2023, pp. 1-13
Druh dokumentu:	Working Paper
DOI:	10.4204/EPTCS.378.1
Popis:	We present a kind inference algorithm for the FREEST programming language. The input to the algorithm is FREEST source code with (possibly part of) kind annotations replaced by kind variables. The algorithm infers concrete kinds for all kind variables. We ran the algorithm on the FREEST test suite by first replacing kind annotation on all type variables by fresh kind variables, and concluded that the algorithm correctly infers all kinds. Non surprisingly, we found out that programmers do not choose the most general kind in 20% of the cases. Comment: In Proceedings PLACES 2023, arXiv:2304.05439
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2304.06396 Zobrazit plný text záznamu View this record from Arxiv