Computer Science
  • Theorems vs. Algorithms

    by Vanessa McHale | Computer Science

    Functional programmers vaunt the Curry-Howard(-Lambek) correspondence, as if it endorses the lambda calculus. In fact, it shows the limitations of computer science.

  • Laziness, A.k.a. Computer Science

    by Vanessa McHale | Computer Science

    An established problem in functional programming is the question of evaluation order (see Hudak, ยง2.2). Haskell offers seq; which allows the programmer to magically introduce dependencies in evaluation order and thence subvert lazy evaluation. Sometimes this is necessary; see the foldl foldl' example.

  • All Programming Languages Should Have Linear Types

    by Vanessa McHale | Computer Science

    Much like all dynamically typed languages are poor statically typed languages, typed functional programming languages (corresponding to intuitionistic logic) are subsumed by linear logic. Girard articulates this unity in the logical context. Let us gloss the functional programming side of things.

  • Linear Types for Manipulating Expressions in the Lambda Calculus

    by Vanessa McHale | Computer Science

    If we wish to preserve global uniqueness of names during \(\beta\)-reduction, we have to \(\alpha\)-rename before each substitution. Consider:

  • Linear Effects Handling

    by Vanessa McHale | Computer Science

    Haskell puts all side effects in the IO monad, which passes around the RealWorld. This is unsatisfactory for a number of reasons, and Haskellers have spilled much ink on effects systems. As I recently noted, there are distinctions in how one handles effects at the logical level: in particular, randomness is different from array writes.