With a blend of software engineering facts and thought-provoking opinions, Fred Brooks offers insight for anyone managing complex projects. These essays draw from his experience as project manager for the IBM System/360 computer family and then for OS/360, its massive software system. Now, 45 years after the initial publication of his book, Brooks has revisited his original ideas and added new thoughts and advice, both for readers already familiar with his work and for readers discovering it for the first time.The added chapters contain (1) a crisp condensation of all the propositions asserted in the original book, including Brooks' central argument in The Mythical Man-Month: that large programming projects suffer management problems different from small ones due to the division of labor; that the conceptual integrity of the product is therefore critical; and that it is difficult but possible to achieve this unity; (2) Brooks' view of these propositions a generation later; (3) a reprint of his classic 1986 paper "No Silver Bullet"; and (4) today's thoughts on the 1986 assertion, "There will be no silver bullet within ten years."

    This internationally recognized standard provides the essential tools to practice project management and deliver organizational results.

    But how do you interpret those packets once you've captured them? And how can those packets help you to better understand what's going on under the hood of your network? Practical Packet Analysis shows how to use Wireshark to capture and then analyze packets as you take an indepth look at real-world packet analysis and network troubleshooting. The way the pros do it.Wireshark (derived from the Ethereal project), has become the world's most popular network sniffing application. But while Wireshark comes with documentation, there's not a whole lot of information to show you how to use it in real-world scenarios. Practical Packet Analysis shows you how to:Use packet analysis to tackle common network problems, such as loss of connectivity, slow networks, malware infections, and more Build customized capture and display filters Tap into live network communication Graph traffic patterns to visualize the data flowing across your network Use advanced Wireshark features to understand confusing packets Build statistics and reports to help you better explain technical network information to non-technical usersBecause net-centric computing requires a deep understanding of network communication at the packet level, Practical Packet Analysis is a must have for any network technician, administrator, or engineer troubleshooting network problems of any kind.

    So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems?In this collection of essays and articles, key members of Google's Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You'll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient--lessons directly applicable to your organization.This book is divided into four sections: Introduction--Learn what site reliability engineering is and why it differs from conventional IT industry practicesPrinciples--Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE)Practices--Understand the theory and practice of an SRE's day-to-day work: building and operating large distributed computing systemsManagement--Explore Google's best practices for training, communication, and meetings that your organization can use

    Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

    It should be labelled 'start here'." --Pieter Jan Stappers, ID-StudioLab, Delft University of Technology

    Did you design your system to survivef a sudden rush of visitors from Digg or Slashdot? Or an influx of real world customers from 100 different countries? Are you ready for a world filled with flakey networks, tangled databases, and impatient users?If you're a developer and don't want to be on call for 3AM for the rest of your life, this book will help.In Release It!, Michael T. Nygard shows you how to design and architect your application for the harsh realities it will face. You'll learn how to design your application for maximum uptime, performance, and return on investment.Mike explains that many problems with systems today start with the design.

    By using objects early to solve interesting problems and defining objects later in the course, Building Java Programs develops programming knowledge for a broad audience. Introduction to Java Programming, Primitive Data and Definite Loops, Introduction to Parameters and Objects, Conditional Execution, Program Logic and Indefinite Loops, File Processing, Arrays, Defining Classes, Inheritance and Interfaces, ArrayLists, Java Collections Framework, Recursion, Searching and Sorting, Graphical User Interfaces. For all readers interested in introductory programming.

    More importantly, this book provides a framework for thinking about computer organization and design that will enable the reader to continue the lifetime of learning necessary for staying at the forefront of this competitive discipline. --John Crawford Intel Fellow Director of Microprocessor Architecture, Intel The performance of software systems is dramatically affected by how well software designers understand the basic hardware technologies at work in a system. Similarly, hardware designers must understand the far reaching effects their design decisions have on software applications. For readers in either category, this classic introduction to the field provides a deep look into the computer. It demonstrates the relationship between the software and hardware and focuses on the foundational concepts that are the basis for current computer design. Using a distinctive learning by evolution approach the authors present each idea from its first principles, guiding readers through a series of worked examples that incrementally add more complex instructions until they ha

    You’ll learn how each of these platform-agnostic patterns work, when they might be useful in the cloud, and what impact they’ll have on your application architecture. You’ll also see an example of each pattern applied to an application built with Windows Azure.The patterns are organized into four major topics, such as scalability and handling failure, and primer chapters provide background on each topic. With the information in this book, you’ll be able to make informed decisions for designing effective cloud-native applications that maximize the value of cloud services, while also paying attention to user experience and operational efficiency.Learn about architectural patterns for:Scalability. Discover the advantages of horizontal scaling. Patterns covered include Horizontally Scaling Compute, Queue-Centric Workflow, and Auto-Scaling.Big data. Learn how to handle large amounts of data across a distributed system. Eventual consistency is explained, along with the MapReduce and Database Sharding patterns.Handling failure. Understand how multitenant cloud services and commodity hardware influence your applications. Patterns covered include Busy Signal and Node Failure.Distributed users. Learn how to overcome delays due to network latency when building applications for a geographically distributed user base. Patterns covered include Colocation, Valet Key, CDN, and Multi-Site Deployment.

     As someone that has used the Bash shell almost daily for over 15 years, I've accumulated several command line "tricks" that have saved me time and frustration. Bash Command Line Pro Tips is a collection of 10 techniques that you can put to use right away to increase your efficiency at the command line. Here is what you will learn by reading Bash Command Line Pro Tips: Tip 1: Tab Completion Tip 2: Change to the Previous Directory Tip 3: Reuse the Last Item from the Previous Command Line Tip 4: Rerun a Command That Starts with a given String Tip 5: Command Substitution Tip 6: Use a for Loop at the Command Line Tip 7: Rerun the Previous Command with Root Privileges Tip 8: Rerun the Previous Command While Substituting a String Tip 9: Reuse a Word on the Same Command Line Tip 10: Fix Typos and Shorten Lengthy Commands with Aliases Scroll up, click the "Buy Now With 1-Click" button to start leaning these powerful Linux Command Line Tips.

    Build hands-on expertise through a series of lessons, exercises, and suggested practices—and help maximize your performance on the job.Provides in-depth, hands-on training you take at your own pace Focuses on job-role-specific expertise for using HTML5, JavaScript, and CSS3 to begin building modern web and Windows 8 apps Features pragmatic lessons, exercises, and practices Creates a foundation of skills which, along with on-the-job experience, can be measured by Microsoft Certification exams such as 70-480 Coverage includes: creating HTML5 documents; implementing styles with CSS3; JavaScript in depth; using Microsoft developer tools; AJAX; multimedia support; drawing with Canvas and SVG; drag and drop functionality; location-aware apps; web storage; offline apps; writing your first simple Windows 8 apps; and other key topics

    No longer is execution speed the sole criterion for judging compiled code. Today, code might be judged on how small it is, how much power it consumes, how well it compresses, or how many page faults it generates. In this evolving environment, the task of building a successful compiler relies upon the compiler writer's ability to balance and blend algorithms, engineering insights, and careful planning. Today's compiler writer must choose a path through a design space that is filled with diverse alternatives, each with distinct costs, advantages, and complexities.Engineering a Compiler explores this design space by presenting some of the ways these problems have been solved, and the constraints that made each of those solutions attractive. By understanding the parameters of the problem and their impact on compiler design, the authors hope to convey both the depth of the problems and the breadth of possible solutions. Their goal is to cover a broad enough selection of material to show readers that real tradeoffs exist, and that the impact of those choices can be both subtle and far-reaching.Authors Keith Cooper and Linda Torczon convey both the art and the science of compiler construction and show best practice algorithms for the major passes of a compiler. Their text re-balances the curriculum for an introductory course in compiler construction to reflect the issues that arise in current practice.

    This Fourth Edition not only keeps this tradition alive, it actually improves on it."--Steve Vinoski, Chief Engineer, Product Innovation, IONA Technologies" The Primer really brings this large and complex language down to size."--Justin Shaw, Senior Member of Technical Staff, Electronic Programs Division, The Aerospace Corporation"It not only gets novices up and running early, but gets them to do so using good programming practices."--Nevin ": -)" Liber, Senior Principal Engineer (C++ developer since 1988)This popular tutorial introduction to standard C++ has been completely updated, reorganized, and rewritten to help programmers learn the language faster and use it in a more modern, effective way.Just as C++ has evolved since the last edition, so has the authors' approach to teaching it. They now introduce the C++ standard library from the beginning, giving readers the means to write useful programs without first having to master every language detail. Highlighting today's best practices, they show how to write programs that are safe, can be built quickly, and yet offer outstanding performance. Examples that take advantage of the library, and explain the features of C++, also show how to make the best use of the language. As in its previous editions, the book's authoritative discussion of fundamental C++ concepts and techniques makes it a valuable resource even for more experienced programmers.Program Faster and More Effectively with This Rewritten ClassicRestructured for quicker learning, using the C++ standard libraryUpdated to teach the most current programming styles and program design techniquesFilled with new learning aids that emphasize important points, warn about common pitfalls, suggest good programming practices, and provide general usage tipsComplete with exercises that reinforce skills learnedAuthoritative and comprehensive in its coverage The source code for the book's extended examples is available on the Web at the address below.www.awprofessional.com/cpp_primer

     Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.