[POPL'22] Enhancing Program Testing with Logarithmic Techniques 🔍

Logarithm and Program Testing
Kuen-Bang Hou (Favonia) and Zhuyang Wang
(University of Minnesota, USA; University of Minnesota, USA)

Abstract: Randomized property-based testing has gained much attention recently, but most frameworks stop short at polymorphic properties. Although Bernardy??et??al. have developed a theory to reduce a wide range of polymorphic properties to monomorphic ones, it relies upon ad-hoc embedding-projection pairs to massage the types into a particular form. This paper skips the embedding-projection pairs and presents a mechanical monomorphization for a general class of polymorphic functions, a step towards automatic testing for polymorphic properties. The calculation of suitable types for monomorphization turns out to be logarithm.

Article: https://doi.org/10.1145/3498726

Supplementary archive: https://doi.org/10.1145/3462305 (Badges: Artifacts Available, Artifacts Evaluated, Reusable)

ORCID: https://orcid.org/0000-0002-2310-3673, https://orcid.org/0000-0001-9347-2151

Submitted to the conference by Zhuyang Wang on 2022-01-03

Video Tags: parametricity, polymorphism, logarithm, popl22main-p764-p, doi:10.1145/3498726, doi:10.1145/3462305, orcid:0000-0002-2310-3673, orcid:0000-0001-9347-2151, Artifacts Available, Artifacts Evaluated, Reusable

Presentation at the POPL 2022 conference, January 16, 2022, https://popl22.sigplan.org/
Sponsored by ACM SIGPLAN, https://www.sigplan.org/

Twitter: https://twitter.com/sigplan