Book Image

F# 4.0 Design Patterns

By : Gene Belitski
Book Image

F# 4.0 Design Patterns

By: Gene Belitski

Overview of this book

Following design patterns is a well-known approach to writing better programs that captures and reuses high-level abstractions that are common in many applications. This book will encourage you to develop an idiomatic F# coding skillset by fully embracing the functional-first F# paradigm. It will also help you harness this powerful instrument to write succinct, bug-free, and cross-platform code. F# 4.0 Design Patterns will start off by helping you develop a functional way of thinking. We will show you how beneficial the functional-first paradigm is and how to use it to get the optimum results. The book will help you acquire the practical knowledge of the main functional design patterns, the relationship of which with the traditional Gang of Four set is not straightforward. We will take you through pattern matching, immutable data types, and sequences in F#. We will also uncover advanced functional patterns, look at polymorphic functions, typical data crunching techniques, adjusting code through augmentation, and generalization. Lastly, we will take a look at the advanced techniques to equip you with everything you need to write flawless code.
Table of Contents (20 chapters)
F# 4.0 Design Patterns
Credits
About the Author
Acknowledgements
About the Reviewer
www.PacktPub.com
Preface

A deep dive into recursion


I've already scratched the surface of recursion in Chapter 3, Basic Functions, showing how the rec modifier changes the scoping of the function definition. This explicit indication allows the function to reference itself before the function body is fully defined. Now I'll show you how recursion can be employed in the right or wrong way so that you can learn to follow the right recursion pattern.

Tail recursion

I would not be breaking new ground by pointing out that a function, recursive or not, as it is implemented these days, consumes a certain amount of resources for local values, argument values, and so forth. A non-recursive function consumes these resources upon being called and releases them upon returning the result. So far, so good.

But what happens when the function calls itself? Each nested call can stash local resources to be released when this particular level of recursion is done. Hence, a deep recursion may temporarily increase resource consumption....