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F# 4.0 Design Patterns

You're reading from   F# 4.0 Design Patterns Solve complex problems with functional thinking

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Product type Paperback
Published in Nov 2016
Publisher Packt
ISBN-13 9781785884726
Length 318 pages
Edition 1st Edition
Languages
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Author (1):
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Gene Belitski Gene Belitski
Author Profile Icon Gene Belitski
Gene Belitski
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Table of Contents (14) Chapters Close

Preface 1. Begin Thinking Functionally 2. Dissecting F# Origins and Design FREE CHAPTER 3. Basic Functions 4. Basic Pattern Matching 5. Algebraic Data Types 6. Sequences - The Core of Data Processing Patterns 7. Advanced Techniques: Functions Revisited 8. Data Crunching – Data Transformation Patterns 9. More Data Crunching 10. Type Augmentation and Generic Computations 11. F# Expert Techniques 12. F# and OOP Principles/Design Patterns 13. Troubleshooting Functional Code

Memoization


The next two relatively advanced topics I will cover somehow resemble the Just  in  Time approach taken outside of the compilation context. With Just in Time (https://en.wikipedia.org/wiki/Just_in_Time), Wikipedia comes up first with a production strategy in manufacturing, where components are delivered immediately before being utilized as a way of being lean on inventory costs.

As a matter of fact, memoization and lazy evaluation complement each other in this lean calculation sense. While laziness allows you not to perform calculations until the result is absolutely required, memoization makes the results of the already performed fat resource expensive calculations reusable by not allowing them to be wasted.

I have already used memoization somewhat when implementing prime number generation earlier in this chapter for covering mutual recursion. An expensively generated sequence was cached there in order to use the already generated elements to find the next ones, which are not...

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