However, ATDD is still widely misunderstood by many practitioners. "ATDD by Example" is the first practical, entry-level, hands-on guide to implementing and successfully applying it. ATDD pioneer Markus Gartner walks readers step by step through deriving the right systems from business users, and then implementing fully automated, functional tests that accurately reflect business requirements, are intelligible to stakeholders, and promote more effective development. Through two end-to-end case studies, Gartner demonstrates how ATDD can be applied using diverse frameworks and languages. Each case study is accompanied by an extensive set of artifacts, including test automation classes, step definitions, and full sample implementations. These realistic examples illuminate ATDD's fundamental principles, show how ATDD fits into the broader development process, highlight tips from Gartner's extensive experience, and identify crucial pitfalls to avoid. Readers will learn to Master the thought processes associated with successful ATDD implementationUse ATDD with Cucumber to describe software in ways businesspeople can understand Test web pages using ATDD toolsBring ATDD to Java with the FitNesse wiki-based acceptance test framework Use examples more effectively in Behavior-Driven Development (BDD)Specify software collaboratively through innovative workshopsImplement more user-friendly and collaborative test automationTest more cleanly, listen to test results, and refactor tests for greater value If you're a tester, analyst, developer, or project manager, this book offers a concrete foundation for achieving real benefits with ATDD now-and it will help you reap even more value as you gain experience.

    However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques that allow programmers to develop their own functional data structures. The author includes both classical data structures, such as red-black trees and binomial queues, and a host of new data structures developed exclusively for functional languages. All source code is given in Standard ML and Haskell, and most of the programs are easily adaptable to other functional languages. This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.

    With this guide, pioneering Go programmer Mark Summerfield shows how to write code that takes full advantage of Go's breakthrough features and idioms. Both a tutorial and a language reference, "Programming in Go" brings together all the knowledge you need to evaluate Go, think in Go, and write high-performance software with Go. Summerfield presents multiple idiom comparisons showing exactly how Go improves upon older languages, calling special attention to Go's key innovations. Along the way, he explains everything from the absolute basics through Go's lock-free channel-based concurrency and its flexible and unusual duck-typing type-safe approach to object-orientation. Throughout, Summerfield's approach is thoroughly practical. Each chapter offers multiple live code examples designed to encourage experimentation and help you quickly develop mastery. Wherever possible, complete programs and packages are presented to provide realistic use cases, as well as exercises. Coverage includes:-- Quickly getting and installing Go, and building and running Go programs -- Exploring Go's syntax, features, and extensive standard library -- Programming Boolean values, expressions, and numeric types -- Creating, comparing, indexing, slicing, and formatting strings -- Understanding Go's highly efficient built-in collection types: slices and maps -- Using Go as a procedural programming language -- Discovering Go's unusual and flexible approach to object orientation -- Mastering Go's unique, simple, and natural approach to fine-grained concurrency -- Reading and writing binary, text, JSON, and XML files -- Importing and using standard library packages, custom packages, and third-party packages -- Creating, documenting, unit testing, and benchmarking custom packages

    At that career level, you’ll no longer be required to work towards the next promotion, and being promoted beyond it is exceptional rather than expected. At that point your career path will branch, and you have to decide between remaining at your current level, continuing down the path of technical excellence to become a Staff Engineer, or switching into engineering management. Of course, the specific titles vary by company, and you can replace “Senior Engineer” and “Staff Engineer” with whatever titles your company prefers. Over the past few years we’ve seen a flurry of books unlocking the engineering management career path, like Camille Fournier’s The Manager’s Path, Julie Zhuo’s The Making of a Manager, Lara Hogan’s Resilient Management and my own, An Elegant Puzzle. The management career isn’t an easy one, but increasingly there are maps available for navigating it. On the other hand, the transition into Staff Engineer, and its further evolutions like Principal and Distinguished Engineer, remains challenging and undocumented. What are the skills you need to develop to reach Staff Engineer? Are technical abilities alone sufficient to reach and succeed in that role? How do most folks reach this role? What is your manager’s role in helping you along the way? Will you enjoy being a Staff Engineer or you will toil for years to achieve a role that doesn’t suit you? "Staff Engineer: Leadership beyond the management track" is a pragmatic look at attaining and operating in these Staff-plus roles.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    It's available on almost every OS--if you master the techniques in this book, you'll never need another text editor. Practical Vim shows you 120 vim recipes so you can quickly learn the editor's core functionality and tackle your trickiest editing and writing tasks. Vim, like its classic ancestor vi, is a serious tool for programmers, web developers, and sysadmins. No other text editor comes close to Vim for speed and efficiency; it runs on almost every system imaginable and supports most coding and markup languages. Learn how to edit text the "Vim way:" complete a series of repetitive changes with The Dot Formula, using one keystroke to strike the target, followed by one keystroke to execute the change. Automate complex tasks by recording your keystrokes as a macro. Run the same command on a selection of lines, or a set of files. Discover the "very magic" switch, which makes Vim's regular expression syntax more like Perl's. Build complex patterns by iterating on your search history. Search inside multiple files, then run Vim's substitute command on the result set for a project-wide search and replace. All without installing a single plugin! You'll learn how to navigate text documents as fast as the eye moves--with only a few keystrokes. Jump from a method call to its definition with a single command. Use Vim's jumplist, so that you can always follow the breadcrumb trail back to the file you were working on before. Discover a multilingual spell-checker that does what it's told.Practical Vim will show you new ways to work with Vim more efficiently, whether you're a beginner or an intermediate Vim user. All this, without having to touch the mouse.What You Need: Vim version 7

    This rapid application development framework and its vast ecosystem of tools let you quickly build new sites and applications with clean, readable code. With this practical guide, Matt Stauffer--a leading teacher and developer in the Laravel community--provides the definitive introduction to one of today's most popular web frameworks.The book's high-level overview and concrete examples will help experienced PHP web developers get started with Laravel right away. By the time you reach the last page, you should feel comfortable writing an entire application in Laravel from scratch.Dive into several features of this framework, including:Blade, Laravel's powerful, custom templating toolTools for gathering, validating, normalizing, and filtering user-provided dataLaravel's Eloquent ORM for working with the application's databasesThe Illuminate request object, and its role in the application lifecyclePHPUnit, Mockery, and PHPSpec for testing your PHP codeLaravel's tools for writing JSON and RESTful APIsInterfaces for file system access, sessions, cookies, caches, and searchTools for implementing queues, jobs, events, and WebSocket event publishingLaravel's specialty packages: Scout, Passport, Cashier, Echo, Elixir, Valet, and Socialite

    In it, developer and life coach John Sonmez addresses a wide range of important "soft" topics, from career and productivity to personal finance and investing, and even fitness and relationships, all from a developer-centric viewpoint.For most software developers, coding is the fun part. The hard bits are dealing with clients, peers, and managers, staying productive, achieving financial security, keeping yourself in shape, and finding true love. This book is here to help.Soft Skills: The software developer's life manual is a guide to a well-rounded, satisfying life as a technology professional. In it, developer and life coach John Sonmez offers advice to developers on important "soft" subjects like career and productivity, personal finance and investing, and even fitness and relationships. Arranged as a collection of 71 short chapters, this fun-to-read book invites you to dip in wherever you like. A Taking Action section at the end of each chapter shows you how to get quick results. Soft Skills will help make you a better programmer, a more valuable employee, and a happier, healthier person.What's InsideBoost your career by building a personal brandJohn's secret ten-step process for learning quicklyFitness advice to turn your geekiness to your advantageUnique strategies for investment and early retirement

    

    The concepts and techniques described are the actual ones used by real game studios like Electronic Arts and Naughty Dog. The examples are often grounded in specific technologies, but the discussion extends way beyond any particular engine or API. The references and citations make it a great jumping off point for those who wish to dig deeper into any particular aspect of the game development process.Intended as the text for a college level series in game programming, this book can also be used by amateur software engineers, hobbyists, self-taught game programmers, and existing members of the game industry. Junior game engineers can use it to solidify their understanding of game technology and engine architecture. Even senior engineers who specialize in one particular field of game development can benefit from the bigger picture presented in these pages.

    Focus is on an in-depth analysis and exposition of not-so-obvious coding errors in the sample code provided. The theme is to answer the questions 'How couild I have automatically detected this bug' and 'How could I have prevented this bug'? Chapters include programmer attitudes, techniques and debugging methodology. A particularly revealing chapter is "Treacheries of the Trade", should be required reading for all C maniacs. The author has been a professional programmer for seventeen years and draws heavily (and candidly) on actual coding problems and practices based on years of experience at Microsoft.

    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

    According to the August Forrester Report, 56 percent of IT managers interviewed at Global 2,500 companies are already using some type of open source software in their infrastructure and another 6 percent will install it in the next two years. This revolutionary model for collaborative software development is being embraced and studied by many of the biggest players in the high-tech industry, from Sun Microsystems to IBM to Intel.The Cathedral & the Bazaar is a must for anyone who cares about the future of the computer industry or the dynamics of the information economy. Already, billions of dollars have been made and lost based on the ideas in this book. Its conclusions will be studied, debated, and implemented for years to come. According to Bob Young, "This is Eric Raymond's great contribution to the success of the open source revolution, to the adoption of Linux-based operating systems, and to the success of open source users and the companies that supply them."The interest in open source software development has grown enormously in the past year. This revised and expanded paperback edition includes new material on open source developments in 1999 and 2000. Raymond's clear and effective writing style accurately describing the benefits of open source software has been key to its success. With major vendors creating acceptance for open source within companies, independent vendors will become the open source story in 2001.

    The problem is that all of those lines of JavaScript code can slow down your apps. This book reveals techniques and strategies to help you eliminate performance bottlenecks during development. You'll learn how to improve execution time, downloading, interaction with the DOM, page life cycle, and more. Yahoo! frontend engineer Nicholas C. Zakas and five other JavaScript experts -- Ross Harmes, Julien Lecomte, Steven Levithan, Stoyan Stefanov, and Matt Sweeney -- demonstrate optimal ways to load code onto a page, and offer programming tips to help your JavaScript run as efficiently and quickly as possible. You'll learn the best practices to build and deploy your files to a production environment, and tools that can help you find problems once your site goes live. Identify problem code and use faster alternatives to accomplish the same task Improve scripts by learning how JavaScript stores and accesses data Implement JavaScript code so that it doesn't slow down interaction with the DOM Use optimization techniques to improve runtime performance Learn ways to ensure the UI is responsive at all times Achieve faster client-server communication Use a build system to minify files, and HTTP compression to deliver them to the browser

    In this one-of-a-kind text, author V. Anton Spraul breaks down the ways that programmers solve problems and teaches you what other introductory books often ignore: how to Think Like a Programmer. Each chapter tackles a single programming concept, like classes, pointers, and recursion, and open-ended exercises throughout challenge you to apply your knowledge. You'll also learn how to:Split problems into discrete components to make them easier to solve Make the most of code reuse with functions, classes, and libraries Pick the perfect data structure for a particular job Master more advanced programming tools like recursion and dynamic memory Organize your thoughts and develop strategies to tackle particular types of problems Although the book's examples are written in C++, the creative problem-solving concepts they illustrate go beyond any particular language; in fact, they often reach outside the realm of computer science. As the most skillful programmers know, writing great code is a creative art—and the first step in creating your masterpiece is learning to Think Like a Programmer.