retronym

tail local.sbt project/local.sbt
==> local.sbt <==
TaskKey[Unit]("printBillOfMaterials") := (Def.taskDyn {
  val proj = thisProject.value
  val filter = ScopeFilter(inProjects(proj.aggregate: _*))
  Def.task {
    (updateSbtClassifiers.value :: update.all(filter).value.toList).flatMap(_.configurations).flatMap(_.modules).flatMap(_.artifacts).flatMap(_._1.url).distinct.foreach(println)
    ()
  }
}).value

melvic-ybanez

What I Didn't Know about Functional Programming until 2020

1. Programming using a series of transformations and aggregations, something I've been doing for years, is known as programming in the map/reduce style.
2. The more abstract the type is, the greater its cardinality, and the smaller the set of operations it supports. So make use of universal quantifiers, particularly by implementing fully parametric functions. They guide you on how to implement their term-level definitions by narrowing down the number of possible implementations. In other words, the type system of Scala (or Haskell, for that matter) is not only great for capturing compile-time errors, but is also capable of leading you to the correct solution.
3. You can encode union types by combining different Scala features such as type constructors, subtyping and implicits, and by taking advantage of the Curry-Howard Isomorphism and De Morgan's Laws for neg

Morendil

The IBM Systems Science Institute

Rubric: Software Engineering : Factual Claims : Defect Cost Increase : Pressman Ratios

Context

Background: I have been researching quantity and quality of empirical evidence underlying claims in software engineering. What do we know, and how well-established is that? See in particular https://leanpub.com/leprechauns which concludes that the answer is in (too) many cases "not much, and poor".

This applies in particular to the "Defect Cost Increase" claim, which is poorly supported by evidence. The claim states that the longer a defect stays undiscovered after being introduced in a software system's artefacts, the more expensive it is to correct.

TimJDFletcher

Forward GnuPG agent from macOS to Linux

On the remote machine

Run gpg once as your to create the directory structure

gpg --list-keys

For headless systemd based hosts

jdegoes

Applied Functional Programming with Scala - Notes

Copyright © 2016-2018 Fantasyland Institute of Learning. All rights reserved.

1. Mastering Functions

A function is a mapping from one set, called a domain, to another set, called the codomain. A function associates every element in the domain with exactly one element in the codomain. In Scala, both domain and codomain are types.

val square : Int => Int = x => x * x