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, by Greg Michaelson Greg Michaelson

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Product details

File Size: 12031 KB

Print Length: 336 pages

Publisher: Dover Publications (April 10, 2013)

Publication Date: March 13, 2013

Sold by: Amazon Digital Services LLC

Language: English

ASIN: B00CWR4USM

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Amazon Best Sellers Rank:

#299,138 Paid in Kindle Store (See Top 100 Paid in Kindle Store)

I've been trying to dive into functional programming, so I bought this book. The first chapter or so was a bit off in my opinion. The author should have covered why lambda calculus was invented and done a better job of giving a general overview. However, after looking up a few things online and getting a handle on it, this turned out to be a really amazing book. The author essentially teaches you how to build an entire programming language from first principles. It's quite a journey, actually. And in the process you actually understand how functional programming works. Knowing only beginner python I was able to follow along quite easily and if anything the author went into too much detail. So I found the pacing to be wonderful and because you understand everything that went on previously, the next part really isn't much of a leap. Many confusing functional programming peculiarities like partially applied functions, prefix notation, it's heavy use of recursion (and how it is applied) is a piece of cake. The book concludes with looking at two real programming languages, both of which are still extremely relevant today, and comparing it to the stuff we've been inventing with lambda calculus. The two example languages are Standard ML (which Haskell is largely derived from, for instance) and Common Lisp (which is the other major functional family of languages around today if you ignore prolog).So even though this is an old book, there's not a whole lot about it that's dated. If anything, it's dated in a very good way: it doesn't use academic language or assume you know a lot of programming concepts (many of which hadn't even been invented, so maybe that's part of it) or anything like that. It's easy to follow along with and lambda calculus is actually kind of fun. It's such a trivially simple method of calculating, but with thought you can create some very high-level math and programming ideas and see how they play out.By the way, no math knowledge is required to understand this book. Honestly, all you really need to know is the basic concept of addition and multiplication since the author will be implementing addition and multiplication functions. Other than that, there's no reason an absolute beginning to math or programming couldn't pick up this book. You might have to read the second chapter a second time after you get the hang of it.I want to give it five stars, but it was hard getting going like I mentioned. However, you can easily overcome that by finding and introductory article online or something. Nothing's perfect, but I'm very glad I bought this book.

The content is great and other reviews cover it well. However, be warned that the mathematical notation typeface is illegibly small on Kindle eReaders (I tried on a modern Paperwhite). Adjusting the font size does not adjust the typeface of the mathematical notation. Unless you plan to read in the browser (or maybe on tablet - I haven't tested that), you probably want to opt for the paperback edition.

This would have to be the BEST book I have read on the theory of Lambda Calculus and how to apply it to functional programming.This is a THEORY book, there is a bit of ML in it (but not much).If you are having issues understanding the Functional Language Paradigm, take a step back and get this book. I struggled for a year trying to understand Functional Programming and after reading this book and going through the exercises, I had a better picture of what to do and could step into Haskell and Erlang easier than before.

This volume will provide a solid foundation in functional programing semantics using the lambda calculus. This is a good second book on functional programing, for the reader desiring a deeper understanding of functional programming in general. The languages that they use in the end are Standard ML and Common Lisp, both of which are used in one form or another. (F/# for example has its foundations in ML). Lazy programming languages like Haskell are not addressed, and this is likely because at the time this book was written those languages were still under development.The coolest part is that this volume shows you how to do everything with lambda calculus, that is with functions. Numbers, booleans, recursion, its all here. Great fun for the right kind of person.

Like Object-Oriented Programming (OOP), Functional Programming (FP) is emerging as a mainstream paradigm for software developers. There are many great books out there that teach you functional programming, but largely neglect the theoretical/mathematical underpinnings. This language-agnostic book fills the gap with regards to the hows-and-whys and origins of functional programming. Apart from being extremely easy to understand and being fairly rigorous for an introductory-level book, this book also outlines the meanings and origins of some of the traditional terms and notations associated with functional programming, such as "consing". It wasn't until I read this book that I felt a sense of enlightenment as to the value of Functional Programming. Without a question, I have emerged as a much better software developer after reading this book.

The book is a good introduction to lambda calculus but the exercises are slightly weird. I think that if the author selected a programming language for the exercises it would be much better.The book is much better than Barendregt's book if you are simply looking to understand some of the concepts behind lambda calculus and not a full blown theoretical exposition of all that lambda calculus has to offer. Personally I just want to learn lambda calculus to help develop my intuition of functional programming languages.

Though I haven't finished the book yet. I like to way the book explains how to think about functional programming from the lambda calculus primitives: name, value, function application; and build from this ground into complex program. The downside is that the book uses abstract programming language, and the reader can depend only imagination and it's harder to understand the late chapters. But I think it's still worth just to read the early chapters. I give me a lot insight :)

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