This one's a keeper." --Robert C. Martin "If you want to be an expert in the state of the art in TDD, you need to understand the ideas in this book."--Michael Feathers Test-Driven Development (TDD) is now an established technique for delivering better software faster. TDD is based on a simple idea: Write tests for your code before you write the code itself. However, this simple idea takes skill and judgment to do well. Now there's a practical guide to TDD that takes you beyond the basic concepts. Drawing on a decade of experience building real-world systems, two TDD pioneers show how to let tests guide your development and "grow" software that is coherent, reliable, and maintainable. Steve Freeman and Nat Pryce describe the processes they use, the design principles they strive to achieve, and some of the tools that help them get the job done. Through an extended worked example, you'll learn how TDD works at multiple levels, using tests to drive the features and the object-oriented structure of the code, and using Mock Objects to discover and then describe relationships between objects. Along the way, the book systematically addresses challenges that development teams encounter with TDD--from integrating TDD into your processes to testing your most difficult features. Coverage includes - Implementing TDD effectively: getting started, and maintaining your momentum throughout the project - Creating cleaner, more expressive, more sustainable code - Using tests to stay relentlessly focused on sustaining quality - Understanding how TDD, Mock Objects, and Object-Oriented Design come together in the context of a real software development project - Using Mock Objects to guide object-oriented designs - Succeeding where TDD is difficult: managing complex test data, and testing persistence and concurrency

    But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

    C. R. Licklider, whose visionary dream of a human-computer symbiosis transformed the course of modern science and led to the development of the personal computer. Reprint.

    This book attempts to capture the engineering wisdom and design philosophy of the UNIX, Linux, and Open Source software development community as it has evolved over the past three decades, and as it is applied today by the most experienced programmers. Eric Raymond offers the next generation of hackers the unique opportunity to learn the connection between UNIX philosophy and practice through careful case studies of the very best UNIX/Linux programs.

    The story of information begins in a time profoundly unlike our own, when every thought and utterance vanishes as soon as it is born. From the invention of scripts and alphabets to the long-misunderstood talking drums of Africa, Gleick tells the story of information technologies that changed the very nature of human consciousness. He provides portraits of the key figures contributing to the inexorable development of our modern understanding of information: Charles Babbage, the idiosyncratic inventor of the first great mechanical computer; Ada Byron, the brilliant and doomed daughter of the poet, who became the first true programmer; pivotal figures like Samuel Morse and Alan Turing; and Claude Shannon, the creator of information theory itself. And then the information age arrives. Citizens of this world become experts willy-nilly: aficionados of bits and bytes. And we sometimes feel we are drowning, swept by a deluge of signs and signals, news and images, blogs and tweets. The Information is the story of how we got here and where we are heading.

    The author's take on the essence of Java as a new programming language and the thorough introduction to Java's features make this a worthwhile tutorial. Thinking in Java begins a little esoterically, with the author's reflections on why Java is new and better. (This book's choice of font for chapter headings is remarkably hard on the eyes.) The author outlines his thoughts on why Java will make you a better programmer, without all the complexity. The book is better when he presents actual language features. There's a tutorial to basic Java types, keywords, and operators. The guide includes extensive source code that is sometimes daunting (as with the author's sample code for all the Java operators in one listing.) As such, this text will be most useful for the experienced developer. The text then moves on to class design issues, when to use inheritance and composition, and related topics of information hiding and polymorphism. (The treatment of inner classes and scoping will likely seem a bit overdone for most readers.) The chapter on Java collection classes for both Java Developer's Kit (JDK) 1.1 and the new classes, such as sets, lists, and maps, are much better. There's material in this chapter that you are unlikely to find anywhere else. Chapters on exception handling and programming with type information are also worthwhile, as are the chapters on the new Swing interface classes and network programming. Although it adopts somewhat of a mixed-bag approach, Thinking in Java contains some excellent material for the object-oriented developer who wants to see what all the fuss is about with Java.

    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

    With the "You Don’t Know JS" book series, you’ll get a more complete understanding of JavaScript, including trickier parts of the language that many experienced JavaScript programmers simply avoid.The series’ first book, Up & Going, provides the necessary background for those of you with limited programming experience. By learning the basic building blocks of programming, as well as JavaScript’s core mechanisms, you’ll be prepared to dive into the other, more in-depth books in the series—and be well on your way toward true JavaScript.With this book you will: Learn the essential programming building blocks, including operators, types, variables, conditionals, loops, and functions Become familiar with JavaScript's core mechanisms such as values, function closures, this, and prototypes Get an overview of other books in the series—and learn why it’s important to understand all parts of JavaScript

    The Text Was Designed To Familiarize Students With The Foundations And Principles Of Computer Science And To Strengthen The Students' Ability To Carry Out Formal And Rigorous Mathematical Arguments. In The New Fourth Edition, Author Peter Linz Has Offered A Straightforward, Uncomplicated Treatment Of Formal Languages And Automata And Avoids Excessive Mathematical Detail So That Students May Focus On And Understand The Underlying Principles. In An Effort To Further The Accessibility And Comprehension Of The Text, The Author Has Added New Illustrative Examples Throughout.

    But what do we really know about the design process? What leads to effective, elegant designs? The Design of Design addresses these questions. These new essays by Fred Brooks contain extraordinary insights for designers in every discipline. Brooks pinpoints constants inherent in all design projects and uncovers processes and patterns likely to lead to excellence. Drawing on conversations with dozens of exceptional designers, as well as his own experiences in several design domains, Brooks observes that bold design decisions lead to better outcomes. The author tracks the evolution of the design process, treats collaborative and distributed design, and illuminates what makes a truly great designer. He examines the nuts and bolts of design processes, including budget constraints of many kinds, aesthetics, design empiricism, and tools, and grounds this discussion in his own real-world examples--case studies ranging from home construction to IBM's Operating System/360. Throughout, Brooks reveals keys to success that every designer, design project manager, and design researcher should know.

    Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.

    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/

    They are vehicles, a series of hypothetical, self-operating machines that exhibit increasingly intricate if not always successful or civilized behavior. Each of the vehicles in the series incorporates the essential features of all the earlier models and along the way they come to embody aggression, love, logic, manifestations of foresight, concept formation, creative thinking, personality, and free will. In a section of extensive biological notes, Braitenberg locates many elements of his fantasy in current brain research.

    The manner in which computers are now able to mimic human thinking is rapidly exceeding human capabilities in everything from chess to picking the winner of a song contest. In the age of machine learning, computers do not strictly need to receive an ‘input command’ to perform a task, but rather ‘input data’. From the input of data they are able to form their own decisions and take actions virtually as a human would. But as a machine, can consider many more scenarios and execute calculations to solve complex problems. This is the element that excites companies and budding machine learning engineers the most. The ability to solve complex problems never before attempted. This is also perhaps one reason why you are looking at purchasing this book, to gain a beginner's introduction to machine learning. This book provides a plain English introduction to the following topics: - Artificial Intelligence - Big Data - Downloading Free Datasets - Regression - Support Vector Machine Algorithms - Deep Learning/Neural Networks - Data Reduction - Clustering - Association Analysis - Decision Trees - Recommenders - Machine Learning Careers This book has recently been updated following feedback from readers. Version II now includes: - New Chapter: Decision Trees - Cleanup of minor errors

    In this book, you'll learn how to become an entrepreneur, driving your career in the direction of your choosing. You'll learn how to build your software development career step by step, following the same path that you would follow if you were building, marketing, and selling a product. After all, your skills themselves are a product. The choices you make about which technologies to focus on and which business domains to master have at least as much impact on your success as your technical knowledge itself--don't let those choices be accidental. We'll walk through all aspects of the decision-making process, so you can ensure that you're investing your time and energy in the right areas. You'll develop a structured plan for keeping your mind engaged and your skills fresh. You'll learn how to assess your skills in terms of where they fit on the value chain, driving you away from commodity skills and toward those that are in high demand. Through a mix of high-level, thought-provoking essays and tactical "Act on It" sections, you will come away with concrete plans you can put into action immediately. You'll also get a chance to read the perspectives of several highly successful members of our industry from a variety of career paths. As with any product or service, if nobody knows what you're selling, nobody will buy. We'll walk through the often-neglected world of marketing, and you'll create a plan to market yourself both inside your company and to the industry in general. Above all, you'll see how you can set the direction of your career, leading to a more fulfilling and remarkable professional life.