A circular program is a program that depends on its own result. It may be surprising that this works at all, but laziness makes it possible if output becomes available sooner than it is required. In this final episode of 2023, which will be longer than usual (probably 45-60 minutes), we will take a look at several examples of...
Welcome to the comedy of errors that is our tale of four tumultuous, yet rewarding, years deploying Haskell in a production environment at Scarf...
Lennart Augustsson gave a talk in the FP seminars at Chalmers, Gothenburg, about his new MicroHaskell....
Hate watching videos? Check out the complementary article, which covers the same content: https://dev.to/zelenya/how-to-introduce-haskell-into-your-company-9ff
Today is #Haskell Unfolder day! In our 13th episode, Edsko and Andres will be discussing the topic of "open recursion".
It is finally time to take a look at how GHC introduces thunks to implement laziness. We first consider ways that thunking can sometimes be viewed as an optimization, then try to understand the source of unnecessary thunking in most Haskell programs.
To better understand some counterintuitive evaluation puzzles, we explore the notion of “demand” as it exists in Haskell and discuss how it influences GHC’s choice of evaluation strategy.
Learn how to combine the best of both TypeScript and Haskell for frontend development. TypeScript developers will learn how to take the reactive principles that made React successful to the next level with pure Functional Reactive Programming (FRP). Haskell developers on the other hand will learn how to easily integrate with the...
Answering the question raised at the end of Part 1, we take a look at how a hypothetical Strict Haskell would tie the compilers hands despite pervasive purity. We also examine how laziness permits optimizations that come with no intrinsic cost and compare its benefits to a strict language with opt-in laziness.
Laziness is a critical but often maligned aspect of Haskell, and as this video argues, it is frequently misunderstood. In this video, Alexis explains how even strict evaluation in imperative programming languages is not always quite as strict as it seems, and how deviating from strictness can often significantly improve...
