From Mathematics to Generic Programming (Paperback)

Alexander A. Stepanov, Daniel E. Rose

買這商品的人也買了...

商品描述

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 more 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 of more effective and elegant code. To demonstrate the crucial role these mathematical principles play in many modern applications, the authors show how to 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 their usefulness 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 use.

 

You will learn about

  • How to generalize a four thousand-year-old algorithm, demonstrating indispensable lessons about clarity and efficiency
  • Ancient paradoxes, beautiful theorems, and the productive tension between continuous and discrete
  • A simple algorithm for finding greatest common divisor (GCD) and modern abstractions that build on it
  • Powerful mathematical approaches to abstraction
  • How abstract algebra provides the idea at the heart of generic programming
  • Axioms, proofs, theories, and models: using mathematical techniques to organize knowledge about your algorithms and data structures
  • Surprising subtleties of simple programming tasks and what you can learn from them
  • How practical implementations can exploit theoretical knowledge

 

Alexander A. Stepanov has been programming since 1972–first in the Soviet Union and, since emigrating in 1977, in the United States. He has programmed operating systems, programming tools, compilers, and libraries. His work on the foundations of programming has been supported by GE, Polytechnic University, Bell Labs, HP, SGI, Adobe, and, since 2009, A9.com, Amazon’s search subsidiary. In 1995, he received the Dr. Dobb’s Journal Excellence in Programming Award for the design of the C++ Standard Template Library.

 

Daniel E. Rose is a research scientist who has held management positions at Apple, AltaVista, Xigo, Yahoo, and A9.com. His research focuses on all aspects of search, ranging from low-level algorithms for index compression to human—computer interaction. Rose led the Apple team that created desktop search for the Mac. He holds a Ph.D. in cognitive science and computer science from the University of California, San Diego, and a B.A. in philosophy from Harvard.

商品描述(中文翻譯)

在這本實質且易於理解的書中,著名軟體設計師亞歷山大·斯捷潘諾夫(Alexander Stepanov)和他的同事丹尼爾·羅斯(Daniel Rose)闡明了泛型編程的原則和其基礎的數學概念,幫助您編寫更簡單且更強大的程式碼。

如果您是一位具有合理程度的程式設計師且具有邏輯思維能力,您已具備所需的背景知識。斯捷潘諾夫和羅斯以非凡的清晰度介紹了相關的抽象代數和數論。他們仔細解釋了數學家首先需要解決的問題,然後展示這些數學解決方案如何轉化為泛型編程和創建更有效和優雅的程式碼。為了展示這些數學原則在許多現代應用中的關鍵作用,作者展示了如何使用這些結果和泛化算法來實現現實世界的公鑰加密系統。

在閱讀本書時,您將掌握有效編程所需的思維過程,並學習如何將狹義構想的算法泛化,以擴大其使用範圍而不損失效率。您還將深入了解數學對編程的價值,這將無論您使用哪種編程語言和範式都非常寶貴。

您將學到以下內容:
- 如何泛化一個四千年歷史的算法,展示關於清晰度和效率的不可或缺的教訓
- 古老的悖論、美麗的定理以及連續和離散之間的生產性張力
- 一個簡單的找到最大公因數(GCD)的算法以及建立在其上的現代抽象
- 強大的數學抽象方法
- 抽象代數提供泛型編程核心思想
- 公理、證明、理論和模型:使用數學技巧組織有關算法和數據結構的知識
- 簡單編程任務的令人驚訝的微妙之處以及您可以從中學到的知識
- 實際實現如何利用理論知識

亞歷山大·A·斯捷潘諾夫自1972年以來一直從事程式設計工作,起初在蘇聯,自1977年移民美國以來一直在美國從事程式設計工作。他曾經參與操作系統、程式設計工具、編譯器和庫的開發。他在程式設計基礎方面的工作得到了通用電氣、理工大學、貝爾實驗室、惠普、SGI、Adobe以及自2009年起的A9.com(亞馬遜的搜索子公司)的支持。1995年,他因設計C++標準模板庫而獲得了《Dr. Dobb's Journal》的程式設計卓越獎。

丹尼爾·E·羅斯是一位研究科學家,曾在蘋果、AltaVista、Xigo、Yahoo和A9.com擔任管理職位。他的研究範圍涵蓋搜索的各個方面,從索引壓縮的低級算法到人機交互。羅斯領導了蘋果團隊開發了Mac的桌面搜索功能。他擁有加利福尼亞大學聖地亞哥分校的認知科學和計算機科學博士學位,以及哈佛大學的哲學學士學位。