Savvy Java developers know that not all testing is created equal. In addition to traditional functional testing, many shops are adopting developer testing techniques such as unit testing. Specific, automated tests are created to verify the accuracy and function of code while or even before it's written - to catch bugs early.Unit Testing in Java teaches how to write good tests that are concise and to the point, useful, and maintainable. This book focuses on tools and practices specific to Java. It introduces emerging techniques like specification by example and behavior-driven development, and shows how to add robust practices into developers' toolkits.Table of ContentsI. FOUNDATIONS1. The promise of good tests2. In search of good3. Test doublesII. CATALOG4. Readability5. Maintainability6. TrustworthinessIII. DIVERSIONS7. Testable design8. Writing tests in other JVM languages9. Speeding up test executionsAppendix A: JUnit primerAppendix B: Extending JUnitIndex

    With the advent of programmable shaders, a wide variety of new algorithms have arisen and evolved over the past few years. This edition discusses current, practical rendering methods used in games and other applications. It also presents a solid theoretical framework and relevant mathematics for the field of interactive computer graphics, all in an approachable style. The authors have made the figures used in the book available for download for fair use.: Download Figures

    Explore applying the Hexagonal Architecture within your application, whether within an open source framework or your own bespoke system. Finally, look into integrating Bounded Contexts, using REST and Messaging approaches.

    By applying the design patterns outlined in this book, you’ll learn how to write flexible and resilient code that’s easier—not harder—to work with as your code base grows.JavaScript has become one of the most widely used—and essential—programming languages for the Web, on both the client-side and server-side. In the real world, JavaScript applications are fragile, and when you change them things often break. Author Eric Elliott shows you how to add features without creating bugs or negatively impacting the rest of your code during the course of building a large JavaScript application.Examine the anatomy of a modern JavaScript applicationLearn best practices for code organization, modularity, and reuseApply Model-View-Controller architectures to client-side web developmentDelve into client-side (browser) and server-side (Node) approachesUse Node to design and program RESTful APIsLearn the processes teams use to build, test, deploy, and scale large JavaScript applicationsExpand your application’s reach through platform targets and internationalization

    Itzik Ben-Gan explains key T-SQL concepts and helps you apply your knowledge with hands-on exercises. The book first introduces T-SQL's roots and underlying logic. Next, it walks you through core topics such as single-table queries, joins, subqueries, table expressions, and set operators. Then the book covers more-advanced data-query topics such as window functions, pivoting, and grouping sets. The book also explains how to modify data, work with temporal tables, and handle transactions, and provides an overview of programmable objects. Microsoft Data Platform MVP Itzik Ben-Gan shows you how to: Review core SQL concepts and its mathematical roots Create tables and enforce data integrity Perform effective single-table queries by using the SELECT statement Query multiple tables by using joins, subqueries, table expressions, and set operators Use advanced query techniques such as window functions, pivoting, and grouping sets Insert, update, delete, and merge data Use transactions in a concurrent environment Get started with programmable objects-from variables and batches to user-defined functions, stored procedures, triggers, and dynamic SQL

    This book presents all the important test design techniques in a single place and in a consistent and easy-to-digest format. An immediately useful handbook for test engineers, developers, quality assurance professionals and requirements and systems analysts, it enables you to: choose the best test case design; find software defects in less time and with fewer resources; and develop optimal strategies that help reduce the likelihood of costly errors. It also assists you in estimating the effort, time and cost of good testing. included, helping you to fully understand the practical applications of these techniques. From well-established techniques such as equivalence classes, boundary value analysis, decision tables and state-transition diagrams, to new techniques like use case testing, pairwise testing and exploratory testing, the book is a usful resource for testing professionals seeking to improve their skills and a handy reference for college-level courses in software test design.

    This report provides a brief yet comprehensive introduction to Python for engineers, researchers, and data scientists who are already familiar with another programming language.Author Jake VanderPlas, an interdisciplinary research director at the University of Washington, explains Python’s essential syntax and semantics, built-in data types and structures, function definitions, control flow statements, and more, using Python 3 syntax.You’ll explore:- Python syntax basics and running Python codeBasic semantics of Python variables, objects, and operators- Built-in simple types and data structures- Control flow statements for executing code blocks conditionally- Methods for creating and using reusable functionsIterators, list comprehensions, and generators- String manipulation and regular expressions- Python’s standard library and third-party modules- Python’s core data science tools- Recommended resources to help you learn more

    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.

    NOTE: this Alpha Edition is missing some chapters and may contain errors. See http://saasbook.info for details.

    Each chapter addresses de-facto standards, popular technologies, and design principles applicable to a wide variety of systems. Complete with chapter summaries, end-of-chapter exercises and bibliographies, Distributed Operating Systems concludes with a set of case studies that provide real-world insights into four distributed operating systems.

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

    Vaughn Vernon couples guided approaches to implementation with modern architectures, highlighting the importance and value of focusing on the business domain while balancing technical considerations.Building on Eric Evans’ seminal book, Domain-Driven Design, the author presents practical DDD techniques through examples from familiar domains. Each principle is backed up by realistic Java examples–all applicable to C# developers–and all content is tied together by a single case study: the delivery of a large-scale Scrum-based SaaS system for a multitenant environment.The author takes you far beyond “DDD-lite” approaches that embrace DDD solely as a technical toolset, and shows you how to fully leverage DDD’s “strategic design patterns” using Bounded Context, Context Maps, and the Ubiquitous Language. Using these techniques and examples, you can reduce time to market and improve quality, as you build software that is more flexible, more scalable, and more tightly aligned to business goals.

    Moms in particular will welcome this trend.  A full 60% wish they had a flexible work option. But companies see advantages too in the way remote work increases their talent pool, reduces turnover, lessens their real estate footprint, and improves the ability to conduct business across multiple time zones, to name just a few advantages.  In Remote, inconoclastic authors Fried and Hansson will convince readers that letting all or part of work teams function remotely is a great idea--and they're going to show precisely how a remote work setup can be accomplished.

    Written for both experienced and new programmers alike, Learning Ruby is a just-get-in-and-drive book -- a hands-on tutorial that offers lots of Ruby programs and lets you know how and why they work, just enough to get you rolling down the road. Interest in Ruby stems from the popularity of Rails, the web development framework that's attracting new devotees and refugees from Java and PHP. But there are plenty of other uses for this versatile language. The best way to learn is to just try the code! You'll find examples on nearly every page of this book that you can imitate and hack. Briefly, this book:Outlines many of the most important features of Ruby Demonstrates how to use conditionals, and how to manipulate strings in Ruby. Includes a section on regular expressions Describes how to use operators, basic math, functions from the Math module, rational numbers, etc. Talks you through Ruby arrays, and demonstrates hashes in detail Explains how to process files with Ruby Discusses Ruby classes and modules (mixins) in detail, including a brief introduction to object-oriented programming (OOP) Introduces processing XML, the Tk toolkit, RubyGems, reflection, RDoc, embedded Ruby, metaprogramming, exception handling, and other topics Acquaints you with some of the essentials of Rails, and includes a short Rails tutorial. Each chapter concludes with a set of review questions, and appendices provide you with a glossary of terms related to Ruby programming, plus reference material from the book in one convenient location. If you want to take Ruby out for a drive, Learning Ruby holds the keys.

    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