With the 97 short and extremely useful tips for programmers in this book, you'll expand your skills by adopting new approaches to old problems, learning appropriate best practices, and honing your craft through sound advice.With contributions from some of the most experienced and respected practitioners in the industry--including Michael Feathers, Pete Goodliffe, Diomidis Spinellis, Cay Horstmann, Verity Stob, and many more--this book contains practical knowledge and principles that you can apply to all kinds of projects.A few of the 97 things you should know:"Code in the Language of the Domain" by Dan North"Write Tests for People" by Gerard Meszaros"Convenience Is Not an -ility" by Gregor Hohpe"Know Your IDE" by Heinz Kabutz"A Message to the Future" by Linda Rising"The Boy Scout Rule" by Robert C. Martin (Uncle Bob)"Beware the Share" by Udi Dahan

    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

    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

    It's used worldwide by companies who need to produce reliable, efficient, and scalable applications. Invest in learning Erlang now.Moore's Law is the observation that the amount you can do on a single chip doubles every two years. But Moore's Law is taking a detour. Rather than producing faster and faster processors, companies such as Intel and AMD are producing multi-core devices: single chips containing two, four, or more processors. If your programs aren't concurrent, they'll only run on a single processor at a time. Your users will think that your code is slow.Erlang is a programming language designed for building highly parallel, distributed, fault-tolerant systems. It has been used commercially for many years to build massive fault-tolerated systems that run for years with minimal failures.Erlang programs run seamlessly on multi-core computers: this means your Erlang program should run a lot faster on a 4 core processor than on a single core processor, all without you having to change a line of code.Erlang combines ideas from the world of functional programming with techniques for building fault-tolerant systems to make a powerful language for building the massively parallel, networked applications of the future.This book presents Erlang and functional programming in the familiar Pragmatic style. And it's written by Joe Armstrong, one of the creators of Erlang.It includes example code you'll be able to build upon. In addition, the book contains the full source code for two interesting applications:A SHOUTcast server which you can use to stream music to every computer in your house, and a full-text indexing and search engine that can index gigabytes of data. Learn how to write programs that run on dozens or even hundreds of local and remote processors. See how to write robust applications that run even in the face of network and hardware failure, using the Erlang programming language.

    So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems?In this collection of essays and articles, key members of Google's Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You'll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient--lessons directly applicable to your organization.This book is divided into four sections: Introduction--Learn what site reliability engineering is and why it differs from conventional IT industry practicesPrinciples--Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE)Practices--Understand the theory and practice of an SRE's day-to-day work: building and operating large distributed computing systemsManagement--Explore Google's best practices for training, communication, and meetings that your organization can use

    You'll learn techniques for implementing specific Web technologies and patterns to solve the needs of a typical company as it grows from modest beginnings to become a global enterprise.Learn basic Web techniques for application integrationUse HTTP and the Web’s infrastructure to build scalable, fault-tolerant enterprise applicationsDiscover the Create, Read, Update, Delete (CRUD) pattern for manipulating resourcesBuild RESTful services that use hypermedia to model state transitions and describe business protocolsLearn how to make Web-based solutions secure and interoperableExtend integration patterns for event-driven computing with the Atom Syndication Format and implement multi-party interactions in AtomPubUnderstand how the Semantic Web will impact systems design

    The book covers lambdas, streams, and functional-style programming. With Java 8's functional features you can now write more concise code in less time, and also automatically benefit from multicore architectures. It's time to dig in!

    Topics are broken down into three major conceptual pieces: Virtualization, Concurrency, and Persistence. Includes all major components of modern systems including scheduling, virtual memory management, disk subsystems and I/O, file systems, and even a short introduction to distributed systems.

    It teaches programming by presenting the concepts in the context of full working programs. The fifth edition reflects suggested improvements.

    But as the field evolves, designers enter the field from many disciplines. Practitioners today have enough experience in UI design that they have been exposed to design rules, but it is essential that they understand the psychology behind the rules in order to effectively apply them. In "Designing with the Mind in Mind," Jeff Johnson, author of the best selling "GUI Bloopers," provides designers with just enough background in perceptual and cognitive psychology that UI design guidelines make intuitive sense rather than being just a list of rules to follow. * The first practical, all-in-one source for practitioners on user interface design rules and why, when and how to apply them.* Provides just enough background into the reasoning behind interface design rules that practitioners can make informed decisions in every project.* Gives practitioners the insight they need to make educated design decisions when confronted with tradeoffs, including competing design rules, time constrictions, or limited resources.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    This introduction is ideal for beginners: it requires no previous programming experience and all concepts are explained from first principles via carefully chosen examples. Each chapter includes exercises that range from the straightforward to extended projects, plus suggestions for further reading on more advanced topics. The author is a leading Haskell researcher and instructor, well-known for his teaching skills. The presentation is clear and simple, and benefits from having been refined and class-tested over several years. The result is a text that can be used with courses, or for self-learning. Features include freely accessible Powerpoint slides for each chapter, solutions to exercises and examination questions (with solutions) available to instructors, and a downloadable code that's fully compliant with the latest Haskell release.

    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.

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    What's been lacking is the expertise to fuse them into solutions to real-world problems. These patterns are the intellectual mortar for J2EE software construction." —John Vlissides, co-author of Design Patterns, the "Gang of Four" book"The authors of Core J2EE Patterns have harvested a really useful set of patterns. They show how to apply these patterns and how to refactor your system to take advantage of them. It's just like having a team of experts sitting at your side."—Grady Booch, Chief Scientist, Rational Software Corporation "The authors do a great job describing useful patterns for application architectures. The section on refactoring is worth the price of the entire book!"—Craig McClanahan, Struts Lead Architect and Specification Lead for JavaServer Faces "Core J2EE Patterns is the gospel that should accompany every J2EE application server...Built upon the in-the-trenches expertise of its veteran architect authors, this volume unites the platform's many technologies and APIs in a way that application architects can use, and provides insightful answers to the whys, whens, and hows of the J2EE platform."—Sean Neville, JRun Enterprise Architect, MacromediaDevelopers often confuse learning the technology with learning to design with the technology. In this book, senior architects from the Sun Java Center share their cumulative design experience on Java 2 Platform, Enterprise Edition (J2EE) technology.The primary focus of the book is on patterns, best practices, design strategies, and proven solutions using the key J2EE technologies including JavaServer Pages(TM) (JSP(TM)), Servlets, Enterprise JavaBeans(TM) (EJB(TM)), and Java(TM) Message Service (JMS) APIs. The J2EE Pattern Catalog with 21 patterns and numerous strategies is presented to document and promote best practices for these technologies.Core J2EE Patterns, Second Edition offers the following: J2EE Pattern Catalog with 21 patterns—fully revised and newly documented patterns providing proven solutions for enterprise applications Design strategies for the presentation tier, business tier, and integration tier Coverage of servlets, JSP, EJB, JMS, and Web Services J2EE technology bad practices Refactorings to improve existing designs using patterns Fully illustrated with UML diagrams Extensive sample code for patterns, strategies, and refactorings