It guides you step by step from simple tests to tests that are maintainable, readable, and trustworthy. It covers advanced subjects like mocks, stubs, and frameworks such as Typemock Isolator and Rhino Mocks. And you'll learn about advanced test patterns and organization, working with legacy code and even untestable code. The book discusses tools you need when testing databases and other technologies. It's written for .NET developers but others will also benefit from this book.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.Table of ContentsThe basics of unit testingA first unit testUsing stubs to break dependenciesInteraction testing using mock objectsIsolation (mock object) frameworksTest hierarchies and organizationThe pillars of good testsIntegrating unit testing into the organizationWorking with legacy code

    The first edition of this book, Programming Perl, hit the shelves in 1990, and was quickly adopted as the undisputed bible of the language. Since then, Perl has grown with the times, and so has this book.Programming Perl is not just a book about Perl. It is also a unique introduction to the language and its culture, as one might expect only from its authors. Larry Wall is the inventor of Perl, and provides a unique perspective on the evolution of Perl and its future direction. Tom Christiansen was one of the first champions of the language, and lives and breathes the complexities of Perl internals as few other mortals do. Jon Orwant is the editor of The Perl Journal, which has brought together the Perl community as a common forum for new developments in Perl.Any Perl book can show the syntax of Perl's functions, but only this one is a comprehensive guide to all the nooks and crannies of the language. Any Perl book can explain typeglobs, pseudohashes, and closures, but only this one shows how they really work. Any Perl book can say that my is faster than local, but only this one explains why. Any Perl book can have a title, but only this book is affectionately known by all Perl programmers as "The Camel."This third edition of Programming Perl has been expanded to cover version 5.6 of this maturing language. New topics include threading, the compiler, Unicode, and other new features that have been added since the previous edition.

    This book is both an example-driven programmer's guide and a keep-on-your-desk reference, with new chapters that explain everything you need to know to get the most out of JavaScript, including:Scripted HTTP and Ajax XML processing Client-side graphics using the canvas tag Namespaces in JavaScript--essential when writing complex programs Classes, closures, persistence, Flash, and JavaScript embedded in Java applicationsPart I explains the core JavaScript language in detail. If you are new to JavaScript, it will teach you the language. If you are already a JavaScript programmer, Part I will sharpen your skills and deepen your understanding of the language.Part II explains the scripting environment provided by web browsers, with a focus on DOM scripting with unobtrusive JavaScript. The broad and deep coverage of client-side JavaScript is illustrated with many sophisticated examples that demonstrate how to:Generate a table of contents for an HTML document Display DHTML animations Automate form validation Draw dynamic pie charts Make HTML elements draggable Define keyboard shortcuts for web applications Create Ajax-enabled tool tips Use XPath and XSLT on XML documents loaded with Ajax And much morePart III is a complete reference for core JavaScript. It documents every class, object, constructor, method, function, property, and constant defined by JavaScript 1.5 and ECMAScript Version 3.Part IV is a reference for client-side JavaScript, covering legacy web browser APIs, the standard Level 2 DOM API, and emerging standards such as the XMLHttpRequest object and the canvas tag.More than 300,000 JavaScript programmers around the world have made this their indispensable reference book for building JavaScript applications."A must-have reference for expert JavaScript programmers...well-organized and detailed."-- Brendan Eich, creator of JavaScript

    By staying current, remaining relevant, and adapting to emerging course needs, this market-leading text has continued to define the operating systems course. This Seventh Edition not only presents the latest and most relevant systems, it also digs deeper to uncover those fundamental concepts that have remained constant throughout the evolution of today's operation systems. With this strong conceptual foundation in place, students can more easily understand the details related to specific systems. New Adaptations * Increased coverage of user perspective in Chapter 1. * Increased coverage of OS design throughout. * A new chapter on real-time and embedded systems (Chapter 19). * A new chapter on multimedia (Chapter 20). * Additional coverage of security and protection. * Additional coverage of distributed programming. * New exercises at the end of each chapter. * New programming exercises and projects at the end of each chapter. * New student-focused pedagogy and a new two-color design to enhance the learning process.

    To grow professionally, you also need soft skills and effective learning techniques. Honing those skills is what this book is all about. Authors Dave Hoover and Adewale Oshineye have cataloged dozens of behavior patterns to help you perfect essential aspects of your craft. Compiled from years of research, many interviews, and feedback from O'Reilly's online forum, these patterns address difficult situations that programmers, administrators, and DBAs face every day. And it's not just about financial success. Apprenticeship Patterns also approaches software development as a means to personal fulfillment. Discover how this book can help you make the best of both your life and your career. Solutions to some common obstacles that this book explores in-depth include:Burned out at work? "Nurture Your Passion" by finding a pet project to rediscover the joy of problem solving.Feeling overwhelmed by new information? Re-explore familiar territory by building something you've built before, then use "Retreat into Competence" to move forward again.Stuck in your learning? Seek a team of experienced and talented developers with whom you can "Be the Worst" for a while. "Brilliant stuff! Reading this book was like being in a time machine that pulled me back to those key learning moments in my career as a professional software developer and, instead of having to learn best practices the hard way, I had a guru sitting on my shoulder guiding me every step towards master craftsmanship. I'll certainly be recommending this book to clients. I wish I had this book 14 years ago!" -Russ Miles, CEO, OpenCredo

    With this book, you'll get a candid and insightful look at how software is constructed and maintained by some of the world's leading practitioners.Titus Winters, Tom Manshreck, and Hyrum K. Wright, software engineers and a technical writer at Google, reframe how software engineering is practiced and taught: from an emphasis on programming to an emphasis on software engineering, which roughly translates to programming over time.You'll learn:Fundamental differences between software engineering and programmingHow an organization effectively manages a living codebase and efficiently responds to inevitable changeWhy culture (and recognizing it) is important, and how processes, practices, and tools come into play

    Weinberg adds new insights and highlights the similarities and differences between now and then. Using a conversational style that invites the reader to join him, Weinberg reunites with some of his most insightful writings on the human side of software engineering.Topics include egoless programming, intelligence, psychological measurement, personality factors, motivation, training, social problems on large projects, problem-solving ability, programming language design, team formation, the programming environment, and much more.Dorset House Publishing is proud to make this important text available to new generations of programmers -- and to encourage readers of the first edition to return to its valuable lessons.

    Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs -- with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate. With this book, you will:Solve a particular coding problem or improve on the performance of an existing solutionQuickly locate algorithms that relate to the problems you want to solve, and determine why a particular algorithm is the right one to useGet algorithmic solutions in C, C++, Java, and Ruby with implementation tipsLearn the expected performance of an algorithm, and the conditions it needs to perform at its bestDiscover the impact that similar design decisions have on different algorithmsLearn advanced data structures to improve the efficiency of algorithmsWith Algorithms in a Nutshell, you'll learn how to improve the performance of key algorithms essential for the success of your software applications.

    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

    Designed for readers who don't need the academic formality, it's a fast and easy computer science guide. It teaches essential concepts for people who want to program computers effectively. First, it introduces discrete mathematics, then it exposes the most common algorithms and data structures. It also shows the principles that make computers and programming languages work.

    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

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    If you're a reasonably proficient programmer who can think logically, you have all the background you'll need. Stepanov and Rose introduce the relevant abstract algebra and number theory with exceptional clarity. They carefully explain the problems mathematicians first needed to solve, and then show how these mathematical solutions translate to generic programming and the creation of more effective and elegant code. To demonstrate the crucial role these mathematical principles play in many modern applications, the authors show how to use these results and generalized algorithms to implement a real-world public-key cryptosystem. As you read this book, you'll master the thought processes necessary for effective programming and learn how to generalize narrowly conceived algorithms to widen their usefulness without losing efficiency. You'll also gain deep insight into the value of mathematics to programming--insight that will prove invaluable no matter what programming languages and paradigms you use. You will learn aboutHow to generalize a four thousand-year-old algorithm, demonstrating indispensable lessons about clarity and efficiencyAncient paradoxes, beautiful theorems, and the productive tension between continuous and discreteA simple algorithm for finding greatest common divisor (GCD) and modern abstractions that build on itPowerful mathematical approaches to abstractionHow abstract algebra provides the idea at the heart of generic programmingAxioms, proofs, theories, and models: using mathematical techniques to organize knowledge about your algorithms and data structuresSurprising subtleties of simple programming tasks and what you can learn from themHow practical implementations can exploit theoretical knowledge

    Full of insights, arguments and philosophical perspectives, the book covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory, computability and complexity theory, quantum computing, cryptography, the information content of quantum states and the interpretation of quantum mechanics. There are also extended discussions about time travel, Newcomb's Paradox, the anthropic principle and the views of Roger Penrose. Aaronson's informal style makes this fascinating book accessible to readers with scientific backgrounds, as well as students and researchers working in physics, computer science, mathematics and philosophy.

    This makes the book random-access: Items are easy to browse and study in whatever order the reader needs. I will be recommending "Effective Python" to students as an admirably compact source of mainstream advice on a very broad range of topics for the intermediate Python programmer. " Brandon Rhodes, software engineer at Dropbox and chair of PyCon 2016-2017" It s easy to start coding with Python, which is why the language is so popular. However, Python s unique strengths, charms, and expressiveness can be hard to grasp, and there are hidden pitfalls that can easily trip you up. " Effective Python " will help you master a truly Pythonic approach to programming, harnessing Python s full power to write exceptionally robust and well-performing code. Using the concise, scenario-driven style pioneered in Scott Meyers best-selling "Effective C++, " Brett Slatkin brings together 59 Python best practices, tips, and shortcuts, and explains them with realistic code examples. Drawing on years of experience building Python infrastructure at Google, Slatkin uncovers little-known quirks and idioms that powerfully impact code behavior and performance. You ll learn the best way to accomplish key tasks, so you can write code that s easier to understand, maintain, and improve. Key features includeActionable guidelines for all major areas of Python 3.x and 2.x development, with detailed explanations and examples Best practices for writing functions that clarify intention, promote reuse, and avoid bugs Coverage of how to accurately express behaviors with classes and objects Guidance on how to avoid pitfalls with metaclasses and dynamic attributes More efficient approaches to concurrency and parallelism Better techniques and idioms for using Python s built-in modules Tools and best practices for collaborative development Solutions for debugging, testing, and optimization in order to improve quality and performance "