Knowing how to create domain-specific languages (DSLs) can give you a huge productivity boost. Instead of writing code in a general-purpose programming language, you can first build a custom language tailored to make you efficient in a particular domain. The key is understanding the common patterns found across language implementations. "Language Design Patterns" identifies and condenses the most common design patterns, providing sample implementations of each. The pattern implementations use Java, but the patterns themselves are completely general. Some of the implementations use the well-known ANTLR parser generator, so readers will find this book an excellent source of ANTLR examples as well. But this book will benefit anyone interested in implementing languages, regardless of their tool of choice. Other language implementation books focus on compilers, which you rarely need in your daily life. Instead, "Language Design Patterns" shows you patterns you can use for all kinds of language applications. You'll learn to create configuration file readers, data readers, model-driven code generators, source-to-source translators, source analyzers, and interpreters. Each chapter groups related design patterns and, in each pattern, you'll get hands-on experience by building a complete sample implementation. By the time you finish the book, you'll know how to solve most common language implementation problems.

Computer Science: An Overview uses broad coverage and clear exposition to present a complete picture of the dynamic computer science field. Accessible to students from all backgrounds, Glenn Brookshear uses a language-independent context to encourage the development of a practical, realistic understanding of the field. An overview of each of the important areas of Computer Science (e.g. Networking, OS, Computer Architecture, Algorithms) provides students with a general level of proficiency for future courses.
The Eleventh Edition features two new contributing authors (David Smith — Indiana University of PA; Dennis Brylow — Marquette University), new, modern examples, and updated coverage based on current technology.

"In most fields the great work is done early on. The paintings made between 1430 and 1500 are still unsurpassed. Shakespeare appeared just as professional theater was being born, and pushed the medium so far that every playwright since has had to live in his shadow. Albrecht Durer did the same thing with engraving, and Jane Austen with the novel.

Essential Information about Algorithms and Data Structures A Classic Reference The latest version of Sedgewick,s best-selling series, reflecting an indispensable body of knowledge developed over the past several decades. Broad Coverage Full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing, including fifty algorithms every programmer should know. See

This new edition of The Art of Prolog contains a number of important changes. Most background sections at the end of each chapter have been updated to take account of important recent research results, the references have been greatly expanded, and more advanced exercises have been added which have been used successfully in teaching the course.Part II, The Prolog Language, has been modified to be compatible with the new Prolog standard, and the chapter on program development has been significantly altered: the predicates defined have been moved to more appropriate chapters, the section on efficiency has been moved to the considerably expanded chapter on cuts and negation, and a new section has been added on stepwise enhancement -- a systematic way of constructing Prolog programs developed by Leon Sterling.All but one of the chapters in Part III, Advanced Prolog Programming Techniques, have been substantially changed, with some major rearrangements. A new chapter on interpreters describes a rule language and interpreter for expert systems, which better illustrates how Prolog should be used to construct expert systems. The chapter on program transformation is completely new and the chapter on logic grammars adds new material for recognizing simple languages, showing how grammars apply to more computer science examples.

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Cython can yield massive performance improvements over pure Python—speedups of 3000X are easily attainable for certain patterns. With this book, Kurt Smith shows you how to use Cython to easily wrap C and C++ libraries in Python, handling all the details of memory management for you. By removing the barrier between Python and C, Cython harnesses the best of both languages while remaining familiar and comfortable to Python users.
Cython has proven its usefulness in many foundational projects: Pandas, SymPy, Sage, and dozens of others, both open and closed source. You'll learn how Cython is an essential part of any performance-oriented Python programmer’s arsenal.

Think Python is an introduction to Python programming for students with no programming experience. It starts with the most basic concepts of programming, and is carefully designed to define all terms when they are first used and to develop each new concept in a logical progression. Larger pieces, like recursion and object-oriented programming are divided into a sequence of smaller steps and introduced over the course of several chapters.

This new and updated edition deals with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics, statistical mechanics, and related fields. After briefly recalling essential background in statistical mechanics and probability theory, it gives a succinct overview of simple sampling methods. The concepts behind the simulation algorithms are explained comprehensively, as are the techniques for efficient evaluation of system configurations generated by simulation. It contains many applications, examples, and exercises to help the reader and provides many new references to more specialized literature. This edition includes a brief overview of other methods of computer simulation and an outlook for the use of Monte Carlo simulations in disciplines beyond physics. This is an excellent guide for graduate students and researchers who use computer simulations in their research. It can be used as a textbook for graduate courses on computer simulations in physics and related disciplines.

This book emphasizes the creative aspects of algorithm design by examining steps used in the process of algorithms development. The heart of this creative process lies in an analogy between proving mathematical theorems by induction and designing combinatorial algorithms. The book contains hundreds of problems and examples. It is designed to enhance the reader's problem-solving abilities and understanding of the principles behind algorithm design.

This book offers robust solutions for everyday programming tasks, providing all the necessary information to
understand and use common programming techniques. It includes implementations and real-world examples of
each data structure in the text and full source code on the accompanying website
(http://examples.oreilly.com/masteralgoc/). Intended for anyone with a basic understanding of the C language.
Preface
When I first thought about writing this book, I immediately thought of O'Reilly & Associates to publish it. They were the first publisher
I contacted, and the one I most wanted to work with because of their tradition of books covering "just the facts." This approach is not
what one normally thinks of in connection with books on data structures and algorithms. When one studies data structures and
algorithms, normally there is a fair amount of time spent on proving their correctness rigorously. Consequently, many books on this
subject have an academic feel about them, and real details such as implementation and application are left to be resolved
elsewhere. This book covers how and why certain data structures and algorithms work, real applications that use them (including
many examples), and their implementation. Mathematical rigor appears only to the extent necessary in explanations.
Naturally, I was very happy that O'Reilly & Associates saw value in a book that covered this aspect of the subject. This preface
contains some of the reasons I think you will find this book valuable as well. It also covers certain aspects of the code in the book,
defines a few conventions, and gratefully acknowledges the people who played a part in the book's creation.
Bookmarks
Main Page
Table of content
Copyright
Preface
Organization
Key Features
About the Code
Conventions
How to Contact Us
Acknowledgments
Part I: Preliminaries
Chapter 1. Introduction
1.1 An Introduction to Data Structures
1.2 An Introduction to Algorithms
1.3 A Bit About Software Engineering
1.4 How to Use This Book
Chapter 2. Pointer Manipulation
2.1 Pointer Fundamentals
2.2 Storage Allocation
2.3 Aggregates and Pointer Arithmetic
2.4 Pointers as Parameters to Functions
2.5 Generic Pointers and Casts
2.6 Function Pointers
2.7 Questions and Answers
2.8 Related Topics
Chapter 3. Recursion
3.1 Basic Recursion
3.2 Tail Recursion
3.3 Questions and Answers
3.4 Related Topics
Chapter 4. Analysis of Algorithms
4.1 Worst-Case Analysis
4.2 O-Notation
4.3 Computational Complexity
4.4 Analysis Example: Insertion Sort
4.5 Questions and Answers
4.6 Related Topics
Part II: Data Structures
Chapter 5. Linked Lists
5.1 Description of Linked Lists
5.2 Interface for Linked Lists
5.3 Implementation and Analysis of Linked Lists
5.4 Linked List Example: Frame Management
5.5 Description of Doubly-Linked Lists
5.6 Interface for Doubly-Linked Lists
5.7 Implementation and Analysis of Doubly Linked Lists
5.8 Description of Circular Lists
5.9 Interface for Circular Lists
5.10 Implementation and Analysis of Circular Lists
5.11 Circular List Example: Second-Chance Page Replacement
5.12 Questions and Answers
5.13 Related Topics
Chapter 6. Stacks and Queues
6.1 Description of Stacks
6.2 Interface for Stacks
6.3 Implementation and Analysis of Stacks
6.4 Description of Queues
6.5 Interface for Queues
6.6 Implementation and Analysis of Queues
6.7 Queue Example: Event Handling
6.8 Questions and Answers
6.9 Related Topics
Chapter 7. Sets
7.1 Description of Sets
7.2 Interface for Sets
7.3 Implementation and Analysis of Sets
7.4 Set Example: Set Covering
7.5 Questions and Answers
7.6 Related Topics
Chapter 8. Hash Tables
8.1 Description of Chained Hash Tables
8.2 Interface for Chained Hash Tables
8.3 Implementation and Analysis of Chained Hash Tables
8.4 Chained Hash Table Example: Symbol Tables
8.5 Description of Open-Addressed Hash Tables
8.6 Interface for Open-Addressed Hash Tables
8.7 Implementation and Analysisof Open Addressed Hash Tables
8.8 Questions and Answers
8.9 Related Topics
Chapter 9. Trees
9.1 Description of Binary Trees
9.2 Interface for Binary Trees
9.3 Implementation and Analysis of Binary Trees
9.4 Binary Tree Example: Expression Processing
9.5 Description of Binary Search Trees
9.6 Interface for Binary Search Trees
9.7 Implementation and Analysis of Binary Search Trees
9.8 Questions and Answers
9.9 Related Topics
Chapter 10. Heaps and Priority Queues
10.1 Description of Heaps
10.2 Interface for Heaps
10.3 Implementation and Analysis of Heaps
10.4 Description of Priority Queues
10.5 Interface for Priority Queues
10.6 Implementation and Analysis of Priority Queues
10.7 Priority Queue Example: Parcel Sorting
10.8 Questions and Answers
10.9 Related Topics
Chapter 11. Graphs
11.1 Description of Graphs
11.2 Interface for Graphs
11.3 Implementation and Analysis of Graphs
11.4 Graph Example: Counting Network Hops
11.5 Graph Example: Topological Sorting
11.6 Questions and Answers
11.7 Related Topics
Part III: Algorithms
Chapter 12. Sorting and Searching
12.1 Description of Insertion Sort
12.2 Interface for Insertion Sort
12.3 Implementation and Analysis of Insertion Sort
12.4 Description of Quicksort
12.5 Interface for Quicksort
12.6 Implementation and Analysis of Quicksort
12.7 Quicksort Example: Directory Listings
12.8 Description of Merge Sort
12.9 Interface for Merge Sort
12.10 Implementation and Analysis of Merge Sort
12.11 Description of Counting Sort
12.12 Interface for Counting Sort
12.13 Implementation and Analysis of Counting Sort
12.14 Description of Radix Sort
12.15 Interface for Radix Sort
12.16 Implementation and Analysis of Radix Sort
12.17 Description of Binary Search
12.18 Interface for Binary Search
12.19 Implementation and Analysis of Binary Search
12.20 Binary Search Example: Spell Checking
12.21 Questions and Answers
12.22 Related Topics
Chapter 13. Numerical Methods
13.1 Description of Polynomial Interpolation
13.2 Interface for Polynomial Interpolation
13.3 Implementation and Analysis of Polynomial Interpolation
13.4 Description of Least-Squares Estimation
13.5 Interface for Least-Squares Estimation
13.6 Implementation and Analysis of Least-Squares Estimation
13.7 Description of the Solution of Equations
13.8 Interface for the Solution of Equations
13.9 Implementation and Analysis of the Solution of Equations
13.10 Questions and Answers
13.11 Related Topics
Chapter 14. Data Compression
14.1 Description of Bit Operations
14.2 Interface for Bit Operations
14.3 Implementation and Analysis of Bit Operations
14.4 Description of Huffman Coding
14.5 Interface for Huffman Coding
14.6 Implementation and Analysis of Huffman Coding
14.7 Huffman Coding Example: Optimized Networking
14.8 Description of LZ77
14.9 Interface for LZ77
14.10 Implementation and Analysis of LZ77
14.11 Questions and Answers
14.12 Related Topics
Chapter 15. Data Encryption
15.1 Description of DES
15.2 Interface for DES
15.3 Implementation and Analysis of DES
15.4 DES Example: Block Cipher Modes
15.5 Description of RSA
15.6 Interface for RSA
15.7 Implementation and Analysis of RSA
15.8 Questions and Answers
15.9 Related Topics
Chapter 16. Graph Algorithms
16.1 Description of Minimum Spanning Trees
16.2 Interface for Minimum Spanning Trees
16.3 Implementation and Analysis of Minimum Spanning Trees
16.4 Description of Shortest Paths
16.5 Interface for Shortest Paths
16.6 Implementation and Analysis of Shortest Paths
16.7 Shortest Paths Example: Routing Tables
16.8 Description of the Traveling-Salesman Problem
16.9 Interface for the Traveling-Salesman Problem
16.10 Implementation and Analysis of the Traveling-Salesman Problem
16.11 Questions and Answers
16.12 Related Topics
Chapter 17. Geometric Algorithms
17.1 Description of Testing Whether Line Segments Intersect
17.2 Interface for Testing Whether Line Segments Intersect
17.3 Implementation and Analysis of Testing Whether Line Segments Intersect
17.4 Description of Convex Hulls
17.5 Interface for Convex Hulls
17.6 Implementation and Analysis of Convex Hulls
17.7 Description of Arc Length on Spherical Surfaces
17.8 Interface for Arc Length on Spherical Surfaces
17.9 Implementation and Analysis of Arc Length on Spherical Surfaces
17.10 Arc Length Example: Approximating Distances on Earth
17.11 Questions and Answers
17.12 Related Topics
Colophon
index

Robert Sedgewick has thoroughly rewritten and substantially expanded and updated his popular work to provide current and comprehensive coverage of important algorithms and data structures. Christopher Van Wyk and Sedgewick have developed new C++ implementations that both express the methods in a concise and direct manner, and also provide programmers with the practical means to test them on real applications. Many new algorithms are presented, and the explanations of each algorithm are much more detailed than in previous editions. A new text design and detailed, innovative figures, with accompanying commentary, greatly enhance the presentation. The third edition retains the successful blend of theory and practice that has made Sedgewick's work an invaluable resource for more than 250,000 programmers! This particular book, Parts 1n4, represents the essential first half of Sedgewick's complete work. It provides extensive coverage of fundamental data structures and algorithms for sorting, searching, and related applications. Although the substance of the book applies to programming in any language, the implementations by Van Wyk and Sedgewick also exploit the natural match between C++ classes and ADT implementations. Highlights * Expanded coverage of arrays, linked lists, strings, trees, and other basic data structures * Greater emphasis on abstract data types (ADTs), modular programming, object-oriented programming, and C++ classes than in previous editions * Over 100 algorithms for sorting, selection, priority queue ADT implementations, and symbol table ADT (searching) implementations * New implementations of binomial queues, multiway radix sorting, randomized BSTs, splay trees, skip lists, multiway tries, B trees, extendible hashing, and much more * Increased quantitative information about the algorithms, giving you a basis for comparing them * Over 1000 new exercises to help you learn the properties of algorithms Whether you are learning the algorithms for the first time or wish to have up-to-date reference material that incorporates new programming styles with classic and new algorithms, you will find a wealth of useful information in this book.

Peter Seibel interviews 15 of the most interesting computer programmers alive today in Coders at Work, offering a companion volume to Apress's highly acclaimed best-seller Founders at Work by Jessica Livingston. As the words "at work" suggest, Peter Seibel focuses on how his interviewees tackle the day-to-day work of programming, while revealing much more, like how they became great programmers, how they recognize programming talent in others, and what kinds of problems they find most interesting. Hundreds of people have suggested names of programmers to interview on the Coders at Work web site: www.codersatwork.com. The complete list was 284 names. Having digested everyone's feedback, we selected 15 folks who've been kind enough to agree to be interviewed: * Frances Allen: Pioneer in optimizing compilers, first woman to win the Turing Award (2006) and first female IBM fellow * Joe Armstrong: Inventor of Erlang * Joshua Bloch: Author of the Java collections framework, now at Google * Bernie Cosell: One of the main software guys behind the original ARPANET IMPs and a master debugger * Douglas Crockford: JSON founder, JavaScript architect at Yahoo! * L. Peter Deutsch: Author of Ghostscript, implementer of Smalltalk-80 at Xerox PARC and Lisp 1.5 on PDP-1 * Brendan Eich: Inventor of JavaScript, CTO of the Mozilla Corporation * Brad Fitzpatrick: Writer of LiveJournal, OpenID, memcached, and Perlbal * Dan Ingalls: Smalltalk implementor and designer * Simon Peyton Jones: Coinventor of Haskell and lead designer of Glasgow Haskell Compiler * Donald Knuth: Author of The Art of Computer Programming and creator of TeX * Peter Norvig: Director of Research at Google and author of the standard text on AI * Guy Steele: Coinventor of Scheme and part of the Common Lisp Gang of Five, currently working on Fortress * Ken Thompson: Inventor of UNIX * Jamie Zawinski: Author of XEmacs and early Netscape/Mozilla hacker What you'll learnHow the best programmers in the world do their jobs! Who this book is for Programmers interested in the point of view of leaders in the field. Programmers looking for approaches that work for some of these outstanding programmers. Table of Contents * Jamie Zawinski * Brad Fitzpatrick * Douglas Crockford * Brendan Eich * Joshua Bloch * Joe Armstrong * Simon Peyton Jones * Peter Norvig * Guy Steele * Dan Ingalls * L Peter Deutsch * Ken Thompson * Fran Allen * Bernie Cosell * Donald Knuth

Even bad code can function. But if code isn’t clean, it can bring a development organization to its knees. Every year, countless hours and significant resources are lost because of poorly written code. But it doesn’t have to be that way.
Noted software expert Robert C. Martin presents a revolutionary paradigm with Clean Code: A Handbook of Agile Software Craftsmanship. Martin has teamed up with his colleagues from Object Mentor to distill their best agile practice of cleaning code “on the fly” into a book that will instill within you the values of a software craftsman and make you a better programmer—but only if you work at it.
What kind of work will you be doing? You’ll be reading code—lots of code. And you will be challenged to think about what’s right about that code, and what’s wrong with it. More importantly, you will be challenged to reassess your professional values and your commitment to your craft.
Clean Code is divided into three parts. The first describes the principles, patterns, and practices of writing clean code. The second part consists of several case studies of increasing complexity. Each case study is an exercise in cleaning up code—of transforming a code base that has some problems into one that is sound and efficient. The third part is the payoff: a single chapter containing a list of heuristics and “smells” gathered while creating the case studies. The result is a knowledge base that describes the way we think when we write, read, and clean code.
Readers will come away from this book understanding
How to tell the difference between good and bad code
How to write good code and how to transform bad code into good code
How to create good names, good functions, good objects, and good classes
How to format code for maximum readability
How to implement complete error handling without obscuring code logic
How to unit test and practice test-driven development
This book is a must for any developer, software engineer, project manager, team lead, or systems analyst with an interest in producing better code.

Computers are ubiquitous yet to many they remain objects of irreducible mystery. This text looks at the question of how today's computers can perform such a variety of tasks if computing is just glorified arithmetic. The author illustrates how the answer lies in the fact that computers are essentially engines of logic and that their hardware and software embody concepts developed over centuries by logicians. "Engines of Logic" gives the reader a clear explanation of how and why computers work.

Writing better software: 30 years of UNIX development wisdom In this book, five years in the making, the author encapsulates three decades of unwritten, hard-won software engineering wisdom. Raymond brings together for the first time the philosophy, design patterns, tools, culture, and traditions that make UNIX home to the world's best and most innovative software, and shows how these are carried forward in Linux and today's open-source movement. Using examples from leading open-source projects, he shows UNIX and Linux programmers how to apply this wisdom in building software that's more elegant, more portable, more reusable, and longer-lived.

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Widely considered one of the best practical guides to programming, Steve McConnells original CODE COMPLETE has been helping developers write better software for more than a decade. Now this classic book has been fully updated and revised with leading-edge practicesand hundreds of new code samplesillustrating the art and science of software construction. Capturing the body of knowledge available from research, academia, and everyday commercial practice, McConnell synthesizes the most effective techniques and must-know principles into clear, pragmatic guidance. No matter what your experience level, development environment, or project size, this book will inform and stimulate your thinkingand help you build the highest quality code. Discover the timeless techniques and strategies that help you: Design for minimum complexity and maximum creativity Reap the benefits of collaborative development Apply defensive programming techniques to reduce and flush out errors Exploit opportunities to refactoror evolvecode, and do it safely Use construction practices that are right-weight for your project Debug problems quickly and effectively Resolve critical construction issues early and correctly Build quality into the beginning, middle, and end of your project
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代码大全(第2版)

Refactoring is about improving the design of existing code. It is the process of changing a software system in such a way that it does not alter the external behavior of the code, yet improves its internal structure. With refactoring you can even take a bad design and rework it into a good one. This book offers a thorough discussion of the principles of refactoring, including where to spot opportunities for refactoring, and how to set up the required tests. There is also a catalog of more than 40 proven refactorings with details as to when and why to use the refactoring, step by step instructions for implementing it, and an example illustrating how it works The book is written using Java as its principle language, but the ideas are applicable to any OO language.