Book Image

Soar with Haskell

By : Tom Schrijvers
Book Image

Soar with Haskell

By: Tom Schrijvers

Overview of this book

With software systems reaching new levels of complexity and programmers aiming for the highest productivity levels, software developers and language designers are turning toward functional programming because of its powerful and mature abstraction mechanisms. This book will help you tap into this approach with Haskell, the programming language that has been leading the way in pure functional programming for over three decades. The book begins by helping you get to grips with basic functions and algebraic datatypes, and gradually adds abstraction mechanisms and other powerful language features. Next, you’ll explore recursion, formulate higher-order functions as reusable templates, and get the job done with laziness. As you advance, you’ll learn how Haskell reconciliates its purity with the practical need for side effects and comes out stronger with a rich hierarchy of abstractions, such as functors, applicative functors, and monads. Finally, you’ll understand how all these elements are combined in the design and implementation of custom domain-specific languages for tackling practical problems such as parsing, as well as the revolutionary functional technique of property-based testing. By the end of this book, you’ll have mastered the key concepts of functional programming and be able to develop idiomatic Haskell solutions.
Table of Contents (23 chapters)
Free Chapter
1
Part 1:Basic Functional Programming
6
Part 2: Haskell-Specific Features
11
Part 3: Functional Design Patterns
16
Part 4: Practical Programming

Lazy memory leaks

One of the main issues with laziness is that it becomes much harder to reason about the order in which different parts of the program are executed. That in itself is not necessarily a problem, but a side effect can be. When a program does not need the result of a computation immediately but may need it later, it holds onto that computation in the form of a thunk. Over time, a build-up of such thunks can arise, and the program may start using excessive amounts of memory for them. In that case, we speak of a memory leak.

The leaking accumulator

In Chapter 3, Recursion, we saw the accumulator-based approach to summing a list:

sumAcc :: [Integer] -> Integer
sumAcc l = go l 0 where
  go :: [Integer] -> Integer -> Integer
  go []     acc = acc
  go (x:xs) acc = go xs (acc + x)

This can also be written using the foldl recursion scheme from Chapter 4, Higher-Order Functions:

sumAcc' :: [Integer...