Generating Well-Typed Terms That Are Not “Useless”

Author:

Frank Justin1ORCID,Quiring Benjamin1ORCID,Lampropoulos Leonidas1ORCID

Affiliation:

1. University of Maryland, College Park, USA

Abstract

Random generation of well-typed terms lies at the core of effective random testing of compilers for functional languages. Existing techniques have had success following a top-down type-oriented approach to generation that makes choices locally, which suffers from an inherent limitation: the type of an expression is often generated independently from the expression itself. Such generation frequently yields functions with argument types that cannot be used to produce a result in a meaningful way, leaving those arguments unused. Such "use-less" functions can hinder both performance, as the argument generation code is dead but still needs to be compiled, and effectiveness, as a lot of interesting optimizations are tested less frequently. In this paper, we introduce a novel algorithm that is significantly more effective at generating functions that use their arguments. We formalize both the "local" and the "nonlocal" algorithms as step-relations in an extension of the simply-typed lambda calculus with type and arguments holes, showing how delaying the generation of types for subexpressions by allowing nonlocal generation steps leads to "useful" functions.

Funder

NSF

Publisher

Association for Computing Machinery (ACM)

Reference38 articles.

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3. Generating constrained random data with uniform distribution

4. Generating Random Well-Typed Featherweight Java Programs Using QuickCheck

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