The book begins with the basic concepts of logic and set theory, to familiarize students with the language of mathematics and how it is interpreted. These concepts are used as the basis for a step-by-step breakdown of the most important techniques used in constructing proofs. To help students construct their own proofs, this new edition contains over 200 new exercises, selected solutions, and an introduction to Proof Designer software. No background beyond standard high school mathematics is assumed. Previous Edition Hb (1994) 0-521-44116-1 Previous Edition Pb (1994) 0-521-44663-5

    Every integrated software development environment in the world--open-source, standards-based, and proprietary--now supports UML and, more importantly, the model-driven approach to software development. This makes learning the newest UML standard, UML 2.0, critical for all software developers--and there isn't a better choice than this clear, step-by-step guide to learning the language."--Richard Mark Soley, Chairman and CEO, OMGIf you're like most software developers, you're building systems that are increasingly complex. Whether you're creating a desktop application or an enterprise system, complexity is the big hairy monster you must manage.The Unified Modeling Language (UML) helps you manage this complexity. Whether you're looking to use UML as a blueprint language, a sketch tool, or as a programming language, this book will give you the need-to-know information on how to apply UML to your project. While there are plenty of books available that describe UML, Learning UML 2.0 will show you how to use it. Topics covered include:Capturing your system's requirements in your model to help you ensure that your designs meet your users' needsModeling the parts of your system and their relationshipsModeling how the parts of your system work together to meet your system's requirementsModeling how your system moves into the real world, capturing how your system will be deployedEngaging and accessible, this book shows you how to use UML to craft and communicate your project's design. Russ Miles and Kim Hamilton have written a pragmatic introduction to UML based on hard-earned practice, not theory. Regardless of the software process or methodology you use, this book is the one source you need to get up and running with UML 2.0.Russ Miles is a software engineer for General Dynamics UK, where he works with Java and Distributed Systems, although his passion at the moment is Aspect Orientation and, in particular, AspectJ. Kim Hamilton is a senior software engineer at Northrop Grumman, where she's designed and implemented a variety of systems including web applications and distributed systems, with frequent detours into algorithms development.

    In this acclaimed reference work, Martin covers everything from the core aspects of working in Photoshop to advanced techniques for professional results. Subjects covered include organizing a digital workflow, improving creativity, output, automating Photoshop, and using Camera RAW. The style of the book is extremely clear, with real examples, diagrams, illustrations, and step-by-step explanations supporting the text throughout. This is, quite simply, the essential reference for photographers of all levels using Photoshop. All DVD content is now available online at http://booksite.focalpress.com/compan... for kindle and eBook readers. * Learn Photoshop the Martin Evening way! Everything you need to know for superb photographic results using Photoshop CS5 * Accompanying DVD includes the images used in the book, as well as QuickTime movie tutorials that show you how to get results fast * Packed with diagrams, step-by-steps, and over 750 color images

    His books have been read by over 1,000,000 people and are #1 best-sellers. His book Beginning Ubuntu Linux recently entered its sixth edition, and picked-up a Linux Journal award along the way. Thomas is also the author of Ubuntu Kung Fu. * * * * * * * * * * * * * * * * * Get to grips with the Ubuntu command-line with this #1 best-selling and concise guide. "Best buck I've spent yet" — Amazon review.* Readable, accessible and easy to understand;* Learn essential Ubuntu vocational skills, or read just for fun;* Covers Ubuntu commands, syntax, the filesystem, plus advanced techniques;* For ANY version of Linux based on Debian, such as Linux Mint--not just Ubuntu!;* Includes BONUS introduction to Ubuntu chapter, plus a glossary appendix and a guide to reading Linux/Unix documentation.

    Monkey has been specifically designed for this book: it's a language that looks a lot like C, has first class functions, closures, strings, hashes and arrays and its only implementation is the one we build in the book.In contrast to text books on interpreters & compilers, the focus of this book is working code. Code is not just found in the appendix -- no, nearly every page contains a snippet! And not only that, but also tests. The code presented in the book is fully tested and the test suite is included.For more information, check out: http://interpreterbook.com/

    He explains why invisible and unmanaged queues are the underlying root cause of poor product development performance. He shows why these queues form and how they undermine the speed, quality, and efficiency in product development.

    In each essay, contributors present a notable software architecture, and analyze what makes it innovative and ideal for its purpose. Some of the engineers in this book reveal how they developed a specific project, including decisions they faced and tradeoffs they made. Others take a step back to investigate how certain architectural aspects have influenced computing as a whole. With this book, you'll discover:How Facebook's architecture is the basis for a data-centric application ecosystem The effect of Xen's well-designed architecture on the way operating systems evolve How community processes within the KDE project help software architectures evolve from rough sketches to beautiful systems How creeping featurism has helped GNU Emacs gain unanticipated functionality The magic behind the Jikes RVM self-optimizable, self-hosting runtime Design choices and building blocks that made Tandem the choice platform in high-availability environments for over two decades Differences and similarities between object-oriented and functional architectural views How architectures can affect the software's evolution and the developers' engagement Go behind the scenes to learn what it takes to design elegant software architecture, and how it can shape the way you approach your own projects, with Beautiful Architecture.

    R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you'll need to accomplish 80 percent of modern data tasks. Lander's self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You'll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you'll construct several complete models, both linear and nonlinear, and use some data mining techniques. By the time you're done, you won't just know how to write R programs, you'll be ready to tackle the statistical problems you care about most. COVERAGE INCLUDES - Exploring R, RStudio, and R packages - Using R for math: variable types, vectors, calling functions, and more - Exploiting data structures, including data.frames, matrices, and lists - Creating attractive, intuitive statistical graphics - Writing user-defined functions - Controlling program flow with if, ifelse, and complex checks - Improving program efficiency with group manipulations - Combining and reshaping multiple datasets - Manipulating strings using R's facilities and regular expressions - Creating normal, binomial, and Poisson probability distributions - Programming basic statistics: mean, standard deviation, and t-tests - Building linear, generalized linear, and nonlinear models - Assessing the quality of models and variable selection - Preventing overfitting, using the Elastic Net and Bayesian methods - Analyzing univariate and multivariate time series data - Grouping data via K-means and hierarchical clustering - Preparing reports, slideshows, and web pages with knitr - Building reusable R packages with devtools and Rcpp - Getting involved with the R global community