Updated to cover Internet Explorer 7, Microsoft's vastly improved browser, this new edition includes content on positioning, lists and generated content, table layout, user interface, paged media, and more.Simply put, Cascading Style Sheets (CSS) is a way to separate a document's structure from its presentation. The benefits of this can be quite profound: CSS allows a much richer document appearance than HTML and also saves time -- you can create or change the appearance of an entire document in just one place; and its compact file size makes web pages load quickly.CSS: The Definitive Guide, 3rd Edition, provides you with a comprehensive guide to CSS implementation, along with a thorough review of all aspects of CSS 2.1. Updated to cover Internet Explorer 7, Microsoft's vastly improved browser, this new edition includes content on positioning, lists and generated content, table layout, user interface, paged media, and more. Author Eric Meyer tackles the subject with passion, exploring in detail each individual CSS property and how it interacts with other properties. You'll not only learn how to avoid common mistakes in interpretation, you also will benefit from the depth and breadth of his experience and his clear and honest style. This is the complete sourcebook on CSS.The 3rd edition contains:Updates to reflect changes in the latest draft version of CSS 2.1Browser notes updated to reflect changes between IE6 and IE7Advanced selectors supported in IE7 and other major browsers includedA new round of technical edits by a fresh set of editorsClarifications and corrected errata, including updated URLs ofreferenced online resources

    The study of type systems--and of programming languages from a type-theoretic perspective--has important applications in software engineering, language design, high-performance compilers, and security.This text provides a comprehensive introduction both to type systems in computer science and to the basic theory of programming languages. The approach is pragmatic and operational; each new concept is motivated by programming examples and the more theoretical sections are driven by the needs of implementations. Each chapter is accompanied by numerous exercises and solutions, as well as a running implementation, available via the Web. Dependencies between chapters are explicitly identified, allowing readers to choose a variety of paths through the material.The core topics include the untyped lambda-calculus, simple type systems, type reconstruction, universal and existential polymorphism, subtyping, bounded quantification, recursive types, kinds, and type operators. Extended case studies develop a variety of approaches to modeling the features of object-oriented languages.

    Now, internationally renowned performance expert Brendan Gregg has brought together proven methodologies, tools, and metrics for analyzing and tuning even the most complex environments. Systems Performance: Enterprise and the Cloud focuses on Linux(R) and Unix(R) performance, while illuminating performance issues that are relevant to all operating systems. You'll gain deep insight into how systems work and perform, and learn methodologies for analyzing and improving system and application performance. Gregg presents examples from bare-metal systems and virtualized cloud tenants running Linux-based Ubuntu(R), Fedora(R), CentOS, and the illumos-based Joyent(R) SmartOS(TM) and OmniTI OmniOS(R). He systematically covers modern systems performance, including the "traditional" analysis of CPUs, memory, disks, and networks, and new areas including cloud computing and dynamic tracing. This book also helps you identify and fix the "unknown unknowns" of complex performance: bottlenecks that emerge from elements and interactions you were not aware of. The text concludes with a detailed case study, showing how a real cloud customer issue was analyzed from start to finish. Coverage includes - Modern performance analysis and tuning: terminology, concepts, models, methods, and techniques - Dynamic tracing techniques and tools, including examples of DTrace, SystemTap, and perf - Kernel internals: uncovering what the OS is doing - Using system observability tools, interfaces, and frameworks - Understanding and monitoring application performance - Optimizing CPUs: processors, cores, hardware threads, caches, interconnects, and kernel scheduling - Memory optimization: virtual memory, paging, swapping, memory architectures, busses, address spaces, and allocators - File system I/O, including caching - Storage devices/controllers, disk I/O workloads, RAID, and kernel I/O - Network-related performance issues: protocols, sockets, interfaces, and physical connections - Performance implications of OS and hardware-based virtualization, and new issues encountered with cloud computing - Benchmarking: getting accurate results and avoiding common mistakes This guide is indispensable for anyone who operates enterprise or cloud environments: system, network, database, and web admins; developers; and other professionals. For students and others new to optimization, it also provides exercises reflecting Gregg's extensive instructional experience.

    It's the expertise you need when your start-up gets an unexpected spike in web traffic, or when a new feature causes your mature application to fail. In this collection of essays and interviews, web veterans such as Theo Schlossnagle, Baron Schwartz, and Alistair Croll offer insights into this evolving field. You'll learn stories from the trenches--from builders of some of the biggest sites on the Web--on what's necessary to help a site thrive.Learn the skills needed in web operations, and why they're gained through experience rather than schoolingUnderstand why it's important to gather metrics from both your application and infrastructureConsider common approaches to database architectures and the pitfalls that come with increasing scaleLearn how to handle the human side of outages and degradationsFind out how one company avoided disaster after a huge traffic delugeDiscover what went wrong after a problem occurs, and how to prevent it from happening againContributors include:John AllspawHeather ChampMichael ChristianRichard CookAlistair CrollPatrick DeboisEric FlorenzanoPaul HammondJustin HuffAdam JacobJacob LoomisMatt MassieBrian MoonAnoop NagwaniSean PowerEric RiesTheo SchlossnagleBaron SchwartzAndrew Shafer

    The preeminent expert in his field, Mr.Black draws upon years of experience as president of both theInternational and American Software Testing Qualifications boardsto offer this extensive resource of all the standards, methods, andtools you'll need.The book covers core testing concepts and thoroughly examinesthe best test management practices and tools of leading hardwareand software vendors. Step-by-step guidelines and real-worldscenarios help you follow all necessary processes and avoidmistakes.Producing high-quality computer hardware and software requirescareful, professional testing; Managing the Testing Process, Third Edition explains how to achieve that by following adisciplined set of carefully managed and monitored practices andprocessesThe book covers all standards, methods, and tools you need forprojects large and smallPresents the business case for testing products and reviews theauthor's latest test assessmentsTopics include agile testing methods, risk-based testing, IEEEstandards, ISTQB certification, distributed and outsourced testing, and moreOver 100 pages of new material and case studies have been addedto this new editionIf you're responsible for managing testing in the real world, Managing the Testing Process, Third Edition is the valuablereference and guide you need.

    But can you also build web sites that are usable by machines? That's where the future lies, and that's what RESTful Web Services shows you how to do. The World Wide Web is the most popular distributed application in history, and Web services and mashups have turned it into a powerful distributed computing platform. But today's web service technologies have lost sight of the simplicity that made the Web successful. They don't work like the Web, and they're missing out on its advantages. This book puts the "Web" back into web services. It shows how you can connect to the programmable web with the technologies you already use every day. The key is REST, the architectural style that drives the Web. This book:Emphasizes the power of basic Web technologies -- the HTTP application protocol, the URI naming standard, and the XML markup language Introduces the Resource-Oriented Architecture (ROA), a common-sense set of rules for designing RESTful web services Shows how a RESTful design is simpler, more versatile, and more scalable than a design based on Remote Procedure Calls (RPC) Includes real-world examples of RESTful web services, like Amazon's Simple Storage Service and the Atom Publishing Protocol Discusses web service clients for popular programming languages Shows how to implement RESTful services in three popular frameworks -- Ruby on Rails, Restlet (for Java), and Django (for Python) Focuses on practical issues: how to design and implement RESTful web services and clients This is the first book that applies the REST design philosophy to real web services. It sets down the best practices you need to make your design a success, and the techniques you need to turn your design into working code. You can harness the power of the Web for programmable applications: you just have to work with the Web instead of against it. This book shows you how.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    Along the way, there is an abundance of traps that one can fall into, which can derail the best-laid plans and put your projects behind schedule.Cem Kaner, James Bach, and Bret Pettichord know this all too well. Between them, they have over fifty years of testing experience, and know what it takes for successful testing. In this groundbreaking new book, they have compiled 293 pieces of experience-tested advice for you to put to work in your testing projects. They reveal insights on how to do the job well, how to manage it, and how to steer clear of common misunderstandings in software testing. Each lesson is an assertion related to software testing, followed by an explanation or example that shows you the how, when, and why of the testing lesson.The ultimate resource for software testers, developers, and managers at every level of expertise, this guidebook also features:- Useful practices and helpful ways of evaluating situations gleaned from over fifty years of combined testing experience from the world's leading software testing experts- Lessons for all key topic areas including test design, test automation, test management, testing strategies, and bug reporting- Advice on how to match the selection of practices to the circumstances of your project

    Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center.Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel, it is a joy to read. Tim Roughgarden Stanford University

    New JVM-based languages like Groovy, Scala, and Clojure are redefining what it means to be a Java developer. The core Standard and Enterprise APIs now co-exist with a large and growing body of open source technologies. Multicore processors, concurrency, and massive data stores require new patterns and approaches to development. And with Java 7 due to release in 2011, there's still more to absorb.The Well-Grounded Java Developer is a unique guide written for developers with a solid grasp of Java fundamentals. It provides a fresh, practical look at new Java 7 features along with the array of ancillary technologies that a working developer will use in building the next generation of business software.

    The aim of The Node Beginner Book is to get you started with developing applications for Node.js, teaching you everything you need to know about advanced JavaScript along the way on 59 pages.

    You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!