Vanessa McHale
  • Q Performance for Data Science

    by Vanessa McHale | Vector Languages

    For data science, élites use use array languages such as J or k. However, Python is ubiquitous and thus one would assume it is capable of the same things.

  • The !-modality Is a Comonad

    by Vanessa McHale | Mathetmatics

    The !-modality is a comonad. In particular, it is a functor; we can lift any function/procedure to work on perennial types with map, \( A \multimap B \vdash !A \multimap !B \).

  • Linting for Concatenative Programming

    by Vanessa McHale | Concatenative Programming

    Concatenative languages lend themselves to rewriting because they do not bind variables and thus do not incur any confusion with renaming/scope (compositional rather than applicative).

  • The Interesting Part of Monadic Effects

    by Vanessa McHale | Haskell

    Monads for effects are familiar to the Haskell programmer; they were introduced by Wadler's "Monads for functional programming" and are the accepted way to work with side effects in a lazy language.

  • Compiler Technologies behind Logics

    by Vanessa McHale | Computer Science

    As I wrote elsewhere, garbage collection—manual memory management correspond to intuitionistic logic—linear logic. So garbage collection is a technology with logical implications.

    |