The Howdy Glossary

Charity is a functional programming language built to support equational reasoning through the use of total and partial functions, pattern matching, dependent types, and type inference. Created by Paliath Narendran, John Slaney, and Deepak Kapur at the University of New Mexico in the early 1990s, it was designed to facilitate proving properties about programs at compile time. One core motivation behind Charity's design is to enable users to express mathematical concepts as executable code effectively. This makes it particularly suitable for teaching purposes by enhancing theoretical understanding of computational processes.

Charity stands out for its specialized emphasis on equational reasoning facilitated by features like total and partial functions, pattern matching, dependent types, and type inference. These features enable users to prove properties about programs at compile time, enhancing formal verification capabilities. Its focus on expressing mathematical concepts directly as executable code distinguishes it from mainstream functional programming languages such as Haskell, OCaml, and Scala. While these languages may offer broader ecosystems and larger communities with extensive libraries and industry adoption, Charity is tailored for educational purposes that bridge theoretical understanding with practical programming skills seamlessly.

Charity’s unique focus makes it distinctively useful for students, educators, and researchers aiming to build strong theoretical foundations in computational processes. By enabling individuals interested in delving deep into equational reasoning through specialized features like total and partial functions combined with formal verification support at compile time, Charity serves as a valuable tool for exploring the intersection of mathematical principles and programming rigorously. Its capability to express mathematical concepts directly as executable code positions Charity effectively for those looking to enhance their understanding of both theory and practical applications within functional programming.