Feynman gave his famous course on computation at the California Institute of Technology, he asked Tony Hey to adapt his lecture notes into a book. Although led by Feynman, the course also featured, as occasional guest speakers, some of the most brilliant men in science at that time, including Marvin Minsky, Charles Bennett, and John Hopfield. Although the lectures are now thirteen years old, most of the material is timeless and presents a “Feynmanesque” overview of many standard and some not-so-standard topics in computer science such as reversible logic gates and quantum computers.

    In User Stories Applied, Mike Cohn provides you with a front-to-back blueprint for writing these user stories and weaving them into your development lifecycle.You'll learn what makes a great user story, and what makes a bad one. You'll discover practical ways to gather user stories, even when you can't speak with your users. Then, once you've compiled your user stories, Cohn shows how to organize them, prioritize them, and use them for planning, management, and testing.User role modeling: understanding what users have in common, and where they differ Gathering stories: user interviewing, questionnaires, observation, and workshops Working with managers, trainers, salespeople and other proxies Writing user stories for acceptance testing Using stories to prioritize, set schedules, and estimate release costs Includes end-of-chapter practice questions and exercises User Stories Applied will be invaluable to every software developer, tester, analyst, and manager working with any agile method: XP, Scrum... or even your own home-grown approach.

    The authors guide you step by step, using construction of a CD database application to give you hands-on experience as you progress from the basic to the complex. You'll start with fundamental concepts like writing Unix programs in C. You'll learn basic system calls, file I/O, interprocess communication, and shell programming. You'll become skilled with the toolkits and libraries for working with user interfaces.The book starts from the basics, explaining how to compile and run your first program. New to this edition are chapters on MySQL(R) access and administration; programming GNOME and KDE; and Linux standards for portable applications. Coverage of kernel programming, device drivers, CVS, grep, and GUI development environments has expanded. This book gives you practical knowledge for real wor ld application.What does this book cover?In this book, you will learn how toDevelop programs to access files and the Linux environment Use the GNU compiler, debugger and other development tools Program data storage aapplications for MySQL and DBM database systems Write programs that take advantage of signals, processes and threads Build graphical user interfaces using both the GTK (for GNOME) and Qt (for KDE) libraries Write device drivers that can be loaded into the Linux kernel Access the network using TCP/IP sockets Write scripts that use grep, regular expressions and other Linux facilities Who is this book for?This book is for programmers with some C or C++ experience, who want to take advantage of the Linux development environment. You should have enough Linux familiarity to have installed and configured users on Linux.

    It presents in a unified manner an introduction to the mathematical theory underlying computer graphic applications. It covers topics of keen interest to students in engineering and computer science: transformations, projections, 2-D and 3-D curve definition schemes, and surface definitions. It also includes techniques, such as B-splines, which are incorporated as part of the software in advanced engineering workstations. A basic knowledge of vector and matrix algebra and calculus is required.

    The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression.Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you're a beginner, R Cookbook will help get you started. If you're an experienced data programmer, it will jog your memory and expand your horizons. You'll get the job done faster and learn more about R in the process.Create vectors, handle variables, and perform other basic functionsInput and output dataTackle data structures such as matrices, lists, factors, and data framesWork with probability, probability distributions, and random variablesCalculate statistics and confidence intervals, and perform statistical testsCreate a variety of graphic displaysBuild statistical models with linear regressions and analysis of variance (ANOVA)Explore advanced statistical techniques, such as finding clusters in your dataWonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language--one practical example at a time.--Jeffrey Ryan, software consultant and R package author

    Peeling Data Structures and Algorithms: * Programming puzzles for interviews * Campus Preparation * Degree/Masters Course Preparation * Instructor's * GATE Preparation * Big job hunters: Microsoft, Google, Amazon, Yahoo, Flip Kart, Adobe, IBM Labs, Citrix, Mentor Graphics, NetApp, Oracle, Webaroo, De-Shaw, Success Factors, Face book, McAfee and many more * Reference Manual for working people