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 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.

    Today, most developers acknowledge the benefits of unit testing and rely on the increasingly sophisticated tools now available. The recently released JUnit 4.5 represents the state of the art in unit testing frameworks, and provides significant new features to improve the Java development process.JUnit in Action, Second Edition is an up-to-date guide to unit testing Java applications (including Java EE applications) using the JUnit framework and its extensions. This book provides techniques for solving real-world problems such as testing AJAX applications, using mocks to achieve testing isolation, in-container testing for Java EE and database applications, and test automation.Written to help readers exploit JUnit 4.5, the book covers recent innovations such as the new annotations that simplify test writing, improved exception handling, and the new assertion methods. You'll also discover how to use JUnit extensions to test new application styles and frameworks including Ajax, OSGi, and HTML-based presentation layers.Using a sample-driven approach, various unit testing strategies are covered, such as how to unit test EJBs, database applications, and web applications. Also addressed are testing strategies using freely available open source frameworks and tools, and how to unit test in isolation with Mock Objects. The book will also bring you up to speed on the latest thinking in TDD, BDD, Continuous Integration, and other practices related to unit testing.

    If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills

    You'll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.To get you started--whether you're on Windows, OS X, or Linux--author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.Discover why the command line is an agile, scalable, and extensible technology. Even if you're already comfortable processing data with, say, Python or R, you'll greatly improve your data science workflow by also leveraging the power of the command line.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on plain text, CSV, HTML/XML, and JSONExplore data, compute descriptive statistics, and create visualizationsManage your data science workflow using DrakeCreate reusable tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelines using GNU ParallelModel data with dimensionality reduction, clustering, regression, and classification algorithms

    This guide offers a friendly way to master Node fundamentals with clear and concise information you can use right away.Built on Google’s V8 JavaScript engine, Node offers high performance and easy scalability for server-side applications. Learning Node walks you through the differences and parallels between client-side and server-side programming, with practical examples of programming and deployment.* Quickly learn how to install and deploy Node* Understand how to use Node and related components to build sites and applications efficiently* Manage Node modules with npm* Create pages easily with template systems* Apply client-side skills, tools, and techniques on the server* Maintain a connection between browser and server with web sockets

    The widespread adoption of agile methods has brought the need for effective testing into the limelight, and agile projects have transformed the role of testers. Much of a tester's function, however, remains largely misunderstood. What is the true role of a tester? Do agile teams actually need members with QA backgrounds? What does it really mean to be an "agile tester?"Two of the industry's most experienced agile testing practitioners and consultants, Lisa Crispin and Janet Gregory, have teamed up to bring you the definitive answers to these questions and many others. In Agile Testing, Crispin and Gregory define agile testing and illustrate the tester's role with examples from real agile teams. They teach you how to use the agile testing quadrants to identify what testing is needed, who should do it, and what tools might help. The book chronicles an agile software development iteration from the viewpoint of a tester and explains the seven key success factors of agile testing.Readers will come away from this book understanding- How to get testers engaged in agile development- Where testers and QA managers fit on an agile team- What to look for when hiring an agile tester- How to transition from a traditional cycle to agile development- How to complete testing activities in short iterations- How to use tests to successfully guide development- How to overcome barriers to test automationThis book is a must for agile testers, agile teams, their managers, and their customers.

    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 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

    

    Readers will learn to understand object-oriented design with inheritance or composition, object aggregation and association, and the difference between interfaces and implementations. Readers will also become more efficient and better thinkers in terms of object-oriented development." This revised edition focuses on interoperability across various technologies, primarily using XML as the communication mechanism. A more detailed focus is placed on how business objects operate over networks, including client/server architectures and web services.

    R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment. You'll not only learn how to program in R, but also how to find the right user-contributed R packages for statistical modeling, visualization, and bioinformatics.The author introduces you to the R environment, including the R graphical user interface and console, and takes you through the fundamentals of the object-oriented R language. Then, through a variety of practical examples from medicine, business, and sports, you'll learn how you can use this remarkable tool to solve your own data analysis problems.Understand the basics of the language, including the nature of R objectsLearn how to write R functions and build your own packagesWork with data through visualization, statistical analysis, and other methodsExplore the wealth of packages contributed by the R communityBecome familiar with the lattice graphics package for high-level data visualizationLearn about bioinformatics packages provided by Bioconductor"I am excited about this book. R in a Nutshell is a great introduction to R, as well as a comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it accessible to anyone working with data, not just professional statisticians."

    It teaches Clojure from the basics to advanced topics using practical, real-world application examples. Blow through the theory and dive into practical matters like unit-testing and environment set-up, all the way through building a scalable web-application using domain-specific languages, Hadoop, HBase, and RabbitMQ. About the TechnologyClojure is a modern Lisp for the JVM, and it has the strengths you'd expect: first-class functions, macros, support for functional programming, and a Lisp-like, clean programming style. About this BookClojure in Action is a practical guide focused on applying Clojure to practical programming challenges. You'll start with a language tutorial written for readers who already know OOP. Then, you'll dive into the use cases where Clojure really shines: state management, safe concurrency and multicore programming, first-class code generation, and Java interop. In each chapter, you'll first explore the unique characteristics of a problem area and then discover how to tackle them using Clojure. Along the way, you'll explore practical matters like architecture, unit testing, and set-up as you build a scalable web application that includes custom DSLs, Hadoop, HBase, and RabbitMQ. What's InsideA fast-paced Clojure tutorial Creating web services with Clojure Scaling through messaging Creating DSLs with Clojure's macro system Test-driven development with Clojure Distributed programming with Clojure, and moreThis book assumes you're familiar with an OO language like Java, C#, or C++ but requires no background in Lisp or Clojure itself.================================== Table of ContentsPART 1 GETTING STARTED Introduction to Clojure A whirlwind tour Building blocks of Clojure Polymorphism with multimethods Clojure and Java interop State and the concurrent world Evolving Clojure through macros PART 2 GETTING REAL Test-driven development and more Data storage with Clojure Clojure and the web Scaling through messaging Data processing with Clojure More on functional programming Protocols, records, and type More macros and DSLs

    This book shows you what writing and maintaining testable JavaScript for the client- or server-side actually entails, whether you’re creating a new application or rewriting legacy code.From methods to reduce code complexity to unit testing, code coverage, debugging, and automation, you’ll learn a holistic approach for writing JavaScript code that you and your colleagues can easily fix and maintain going forward. Testing JavaScript code is complicated. This book helps you simply the process considerably.Get an overview of Agile, test-driven development, and behavior-driven developmentUse patterns from static languages and standards-based JavaScript to reduce code complexityLearn the advantages of event-based architectures, including modularity, loose coupling, and reusabilityExplore tools for writing and running unit tests at the functional and application levelGenerate code coverage to measure the scope and effectiveness of your testsConduct integration, performance, and load testing, using Selenium or CasperJSUse tools for in-browser, Node.js, mobile, and production debuggingUnderstand what, when, and how to automate your development processes