(E–pub Download) From Mathematics to Generic Programming
E marched together towards perfection Joseph Louis LagrangeWhat does geometry abstract algebra number theory and generic programming have in common This book attempts to answer that by starting at the early stages of organized mathematics and going all the way forward to the 1960 s The way I thought about Stepanov s approach is that he attempts to generalize algorithms and shows how algorithms in many respects can be sed as axioms In other words generalization is not just merely a time saver but crucially is a way to ensure rigorousness Mathematics is a game played according to certain simple rules with meaningless marks on Paper David HilbertIn Many Ways David HilbertIn many ways book IS JUST STEPANOV REMOVING THE PAPER just Stepanov removing the paper fact that he Dance With The Devil uses C code is irrelevant Ised Python and Java without having Smitten used C in years and it was sufficiently trivial that I could follow along The Euclidean algorithmgreatest common denominator is the main tool of Stepanov of this book may besed too much Algorithms have exist For those of s who need a refresher and a bit Computer programming is a wholly mathematical pursuit Although many computer science departments are housed in engineering the heart and soul is abstract mathematics This book reminds s that a comput.
effective and code To demonstrate the crucial role these mathematical principles play in many modern applications the authors show how to 1898 use these results and generalized algorithms to implement a real world public key cryptosystem As you read this book you'll master the thought processes necessary for effective programming and learn how to generalize narrowly conceived algorithms to widen theirsefulness without losing efficiency You'll also gain deep insight into the value of mathematics to programming insight that will prove invaluable no matter what programming languages and paradigms you se You will learn aboutHow to generalize a four thousan. I expected this book to be written *in aof effective and
popular science Instead chapters were burdened with mathematics and hardcore algorithm optimization Sometimes *a bit popular science way Instead chapters were burdened with mathematics and hardcore algorithm optimization Sometimes author s obsession with nice and sleek programs was getting in the way of clearer explanation Very cool book which builds a bridge between abstract algebra and template functions of clearer explanation Very cool book which builds a bridge between abstract algebra and template functions C Well explained material with engaging history and C code Depends on what you expectI was very enthusiastic about this book when it was first announced My expectation was that author will give some introduction to mathematical constructs related to program composition that comes from category theory and functional programming like monads applicatives traversables and so on Instead I found all familiar view on algebra things ike groups rings some number theory and cryptography However despite my Not the best to learn Number Theory and Algebra from really reuires you to have some knowledge of these in the first place I think the overall concept is interesting but it didn t feel revolutionizing to me As long as algebra and geometry have been separated their progress have been slow and their ses limited but when these two sciences have been nited they have lent each mutual forces and hav. In this substantive yet accessible book pioneering software designer Alexander Stepanov and his colleague Daniel Rose illuminate the principles of generic programming and the mathematical concept of abstraction on which it is based helping you write code that is both simpler and powerful If you're a reasonably proficient programmer who can think logically you have all the background you'll need Stepanov and Rose introduce the relevant abstract algebra and number theory with exceptional clarity They carefully explain the problems mathematicians first needed to solve and then show how these mathematical solutions translate to generic programming and the creation. .bit popular science
Alexander A. Stepanov ð 5 characters,
Er only does what it is told to do and told in a proper fashion While the present tends fall towards AI this book takes a decidedly different tact It gives s the rudimentary basics of computer sec I wonder what s p with
C Concepts these days A worthy follow p to Elements of Programming Where Elements was terse like an old mathConcepts these days A worthy follow Beyond the Qumran Community up to Elements of Programming Where Elements was terse like an old math this book is conversational and it includes short biographies about some of the mathematicians mentioned in the text Includes by way of proofs than Elements Includes a handful of programming laws such as the law ofseful return if you ve gone through the trouble of calculating something consider returning ve gone through the trouble of calculating something consider returning even if your current callers will ignore the return valueIn an interview Stepanov said It is as if mathematicians would start with axioms You do not start with axioms you start with proofs Only when you have found a bunch of related proofs can you come Daniels Pet up with axioms You end with axioms Since all math textbooks I ve eversed started with axioms I was curious to see how things could be different This book stands as a great example of just that the authors don t point that out Losing Control until near the end I am considering sending copies to some friends and relatives not all programmers or mathematicians. D year old algorithm demonstrating indispensable lessons about clarity and efficiencyAncient paradoxes beautiful theorems and the productive tension between continuous and discreteA simple algorithm for finding greatest common divisor GCD and modern abstractions that build on itPowerful mathematical approaches to abstractionHow abstract algebra provides the idea at the heart of generic programmingAxioms proofs theories and modelssing mathematical techniues to organize knowledge about your algorithms and data structuresSurprising subtleties of simple programming tasks and what you can learn from themHow practical implementations can exploit theoretical knowled.