They get frustrated losing their scroll position; they get annoyed waiting for refresh; they struggle to reorient themselves on every new page. And the list goes on. With asynchronous JavaScript and XML, known as "Ajax," you can give them a better experience. Once users have experienced an Ajax interface, they hate to go back. Ajax is new way of thinking that can result in a flowing and intuitive interaction with the user.Ajax in Action helps you implement that thinking--it explains how to distribute the application between the client and the server (hint: use a "nested MVC" design) while retaining the integrity of the system. You will learn how to ensure your app is flexible and maintainable, and how good, structured design can help avoid problems like browser incompatibilities. Along the way it helps you unlearn many old coding habits. Above all, it opens your mind to the many advantages gained by placing much of the processing in the browser. If you are a web developer who has prior experience with web technologies, this book is for you. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

    The best description of the first edition comes from two Amazon reviewers; the first proclaiming, "I got the same feeling of enlightenment when reading this one as I did all those years ago when I read the classic book "Code Complete" and the second stating "This is the first game book I have read that I was sorry when I got to the end because there wasn't any more."For Game Coding Complete, Second Edition, McShaffry returns with many more of his highly popular, shoot-from the hips war stories and expert game programming insight that only a real insider could provide. McShaffry uses his experience as a leading programmer for Origin Systems, Microsoft, and Ion Storm a division of Eidos, to illustrate real-world techniques and solutions, including examples from his recent work on the major game, Thief Deadly Shadows. Game Coding Complete, Second Edition takes programmers through the complete process of developing a professional quality game using hundreds of insider tricks and techniques developed and perfect by the author from over a decade of game development experience. It covers a range of topics that will appeal to the most discriminating programmers such as key "gotcha" issues that could trip up even veteran programmers. The new edition features expanded coverage of 3D programming, several new chapters on game interface design, game audio, game scripting, game engine technology, code optimization, production and scheduling, plus it now includes a CD-ROM packed with valuable source code and game development tools. The appendix offers solid advice on starting your own game company. The C++ language is used to explain specific programming concepts with added discussion of development with C# and Managed DirectX programming.

    Johnson. It was the first book exclusively on the theory of NP-completeness and computational intractability. The book features an appendix providing a thorough compendium of NP-complete problems (which was updated in later printings of the book). The book is now outdated in some respects as it does not cover more recent development such as the PCP theorem. It is nevertheless still in print and is regarded as a classic: in a 2006 study, the CiteSeer search engine listed the book as the most cited reference in computer science literature.

    

    

    

    It offers a comprehensive and accessible treatment of the theory of algorithms and complexity—the elegant body of concepts and methods developed by computer scientists over the past 30 years for studying the performance and limitations of computer algorithms. The book is self-contained in that it develops all necessary mathematical prerequisites from such diverse fields such as computability, logic, number theory and probability.

    From explaining port scanning basics for novices to detailing low-level packet crafting methods used by advanced hackers, this book suits all levels of security and networking professionals. A 42-page reference guide documents every Nmap feature and option, while the rest of the book demonstrates how to apply those features to quickly solve real-world tasks. Examples and diagrams show actual communication on the wire. Topics include subverting firewalls and intrusion detection systems, optimizing Nmap performance, and automating common networking tasks with the Nmap Scripting Engine. Hints and instructions are provided for common uses such as taking network inventory, penetration testing, detecting rogue wireless access points, and quashing network worm outbreaks. Nmap runs on Windows, Linux, and Mac OS X.Nmap's original author, Gordon "Fyodor" Lyon, wrote this book to share everything he has learned about network scanning during more than 11 years of Nmap development. Visit http: //nmap.org/book for more information and sample chapters.

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    It has become popular in recent years because of its simplicity, conciseness, and clarity. This book teaches functional programming as a way of thinking and problem solving, using Haskell, the most popular purely functional language. Rather than using the conventional (boring) mathematical examples commonly found in other programming language textbooks, the author uses examples drawn from multimedia applications, including graphics, animation, and computer music, thus rewarding the reader with working programs for inherently more interesting applications. Aimed at both beginning and advanced programmers, this tutorial begins with a gentle introduction to functional programming and moves rapidly on to more advanced topics. Details about progamming in Haskell are presented in boxes throughout the text so they can be easily found and referred to.

    Sipser's candid, crystal-clear style allows students at every level to understand and enjoy this field. His innovative "proof idea" sections explain profound concepts in plain English. The new edition incorporates many improvements students and professors have suggested over the years, and offers updated, classroom-tested problem sets at the end of each chapter.

    Create a tiny virtual environment, called a container, for your application that includes only its particular set of dependencies. The Docker engine accounts for, manages, and builds these containers through functionality provided by the host operating system. Software running inside containers share the Linux OS and other resources, such as libraries, making their footprints radically smaller, and the containerized applications are easy to install, manage, and remove. Developers can package their applications without worrying about environment-specific deployment concerns, and the operations team gets cleaner, more efficient systems across the board. Better still, Docker is free and open source.Docker in Action teaches readers how to create, deploy, and manage applications hosted in Docker containers. The book starts with a clear explanation of the Docker model of virtualization, comparing this approach to the traditional hypervisor model. Developers will learn how to package applications in containers, including specific techniques for testing and distributing applications via Docker Hub and other registries. Readers will learn how to take advantage of the Linux OS features that Docker uses to run programs securely, and how to manage shared resources. Using carefully-designed examples, the book teaches you how to orchestrate containers and applications from installation to removal. Along the way, you'll learn techniques for using Docker on systems ranging from your personal dev-and-test machine to full-scale cloud deployments.

    But while most of us today can work a computer--albeit with the help of the ever-present computer software manual--we know little about what goes on inside the box and virtually nothing about software designor the world of computer programming. In Patterns of Software, the respected software pioneer and computer scientist, Richard Gabriel, gives us an informative inside look at the world of software design and computer programming and the business that surrounds them. In this wide-ranging volume, Gabriel discusses such topics as whatmakes a successful programming language, how the rest of the world looks at and responds to the work of computer scientists, how he first became involved in computer programming and software development, what makes a successful software business, and why his own company, Lucid, failed in 1994, tenyears after its inception. Perhaps the most interesting and enlightening section of the book is Gabriel's detailed look at what he believes are the lessons that can be learned from architect Christopher Alexander, whose books--including the seminal A Pattern Language--have had a profound influence on the computer programmingcommunity. Gabriel illuminates some of Alexander's key insights--the quality without a name, pattern languages, habitability, piecemeal growth--and reveals how these influential architectural ideas apply equally well to the construction of a computer program. Gabriel explains the concept ofhabitability, for example, by comparing a program to a New England farmhouse and the surrounding structures which slowly grow and are modified according to the needs and desires of the people who live and work on the farm. Programs live and grow, and their inhabitants--the programmers--need to workwith that program the way the farmer works with the homestead. Although computer scientists and software entrepreneurs will get much out of this book, the essays are accessible to everyone and will intrigue anyone curious about Silicon Valley, computer programming, or the world of high technology.

    Hibernate, the most popular Java persistence tool, provides automatic and transparent object/relational mapping making it a snap to work with SQL databases in Java applications. Hibernate applications are cheaper, more portable, and more resilient to change. Because it conforms to the new EJB 3.0 and Java Persistence 1.0 standard, Hibernate allows the developer to seamlessly create efficient, scalable Java EE applications.Java Persistence with Hibernate explores Hibernate by developing an application that ties together hundreds of individual examples. You'll immediately dig into the rich programming model of Hibernate 3.2 and Java Persistence, working through queries, fetching strategies, caching, transactions, conversations, and more. You'll also appreciate the well-illustrated discussion of best practices in database design, object/relational mapping, and optimization techniques.In this revised edition of the bestselling Hibernate in Action, authors Christian Bauer and Gavin King-the founder of the Hibernate project-cover Hibernate 3.2 in detail along with the EJB 3.0 and Java Persistence standard.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.