Be part of the solution. With this practical book, you'll learn 10 easy-to-follow guidelines for delivering software that's easy to maintain and adapt. These guidelines have been derived from analyzing hundreds of real-world systems.Written by consultants from the Software Improvement Group (SIG), this book provides clear and concise explanations, with advice for turning the guidelines into practice. Examples are written in Java, but this guide is equally useful for developers working in other programming languages.10 Coding Guidelines- Write short units of code: limit the length of methods and constructors- Write simple units of code: limit the number of branch points per method- Write code once, rather than risk copying buggy code- Keep unit interfaces small by extracting parameters into objects- Separate concerns to avoid building large classes- Couple architecture components loosely- Balance the number and size of top-level components in your code- Keep your codebase as small as possible- Automate tests for your codebase- Write clean code, avoiding "code smells" that indicate deeper problemsWhy you should read this bookTaken in isolation, the guidelines presented in this book are well-known. In fact, many well-known tools for code analysis check a number of the guidelines presented here. The following three characteristics set this book apart from other books on software development: We have selected the ten most important guidelines from experience.We teach how to comply with these ten guidelines.We present statistics and examples from real-world systems.This book is part our Training on Software Maintainability - and subsequent Certification on Quality Software Development program. For more information about this program, please contact training@sig.eu.

    After splitting a monolithic application or building a microservice ecosystem from scratch, many engineers are left wondering what s next. In this practical book, author Susan Fowler presents a set of microservice standards in depth, drawing from her experience standardizing over a thousand microservices at Uber. You ll learn how to design microservices that are stable, reliable, scalable, fault tolerant, performant, monitored, documented, and prepared for any catastrophe.Explore production-readiness standards, including:Stability and Reliability: develop, deploy, introduce, and deprecate microservices; protect against dependency failuresScalability and Performance: learn essential components for achieving greater microservice efficiencyFault Tolerance and Catastrophe Preparedness: ensure availability by actively pushing microservices to fail in real timeMonitoring: learn how to monitor, log, and display key metrics; establish alerting and on-call proceduresDocumentation and Understanding: mitigate tradeoffs that come with microservice adoption, including organizational sprawl and technical debt"

    Starting with basic examples, this book is focused solely on Java 8 language changes and related API changes, so you don’t need to buy and read a 900 page book in order to brush up. Lambdas make a programmer's job easier, and this book will teach you how. Coverage includes introductory syntax for lambda expressions, method references that allow you to reuse existing named methods from your codebase, and the collection library in Java 8.

    The library is not self-explanatory or fully consistent, and there are still some traps for the unwary. But the advantages far outweigh the problems, especially if you've got an expert book like Nicolai Josuttis' C++ Standard Library to help you. Josuttis starts with an overview of the standard library, and its key interrelationships with the core language. He presents detailed coverage of the STL, the most powerful, complex, and exciting part of the library; then covers special containers, strings, numeric classes, and internationalization; and helps you get more out of a component you're probably already using: the IOStream library. Every component description includes purpose, design, code examples, practical scenarios, pitfalls, and in most cases, reference sources. Whether you need a tutorial or reference, this book delivers the goods.— (Bill Camarda, bn.com, editor)

    If you're working with a relational database--whether you're writing applications, performing administrative tasks, or generating reports--you need to know how to interact with your data. Even if you are using a tool that generates SQL for you, such as a reporting tool, there may still be cases where you need to bypass the automatic generation feature and write your own SQL statements.To help you attain this fundamental SQL knowledge, look to "Learning SQL," an introductory guide to SQL, designed primarily for developers just cutting their teeth on the language."Learning SQL" moves you quickly through the basics and then on to some of the more commonly used advanced features. Among the topics discussed: The history of the computerized databaseSQL Data Statements--those used to create, manipulate, and retrieve data stored in your database; example statements include select, update, insert, and deleteSQL Schema Statements--those used to create database objects, such as tables, indexes, and constraintsHow data sets can interact with queriesThe importance of subqueriesData conversion and manipulation via SQL's built-in functionsHow conditional logic can be used in Data StatementsBest of all, "Learning SQL" talks to you in a real-world manner, discussing various platform differences that you're likely to encounter and offering a series of chapter exercises that walk you through the learning process. Whenever possible, the book sticks to the features included in the ANSI SQL standards. This means you'll be able to apply what you learn to any of several different databases; the book covers MySQL, Microsoft SQL Server, and Oracle Database, but the features and syntax should apply just as well (perhaps with some tweaking) to IBM DB2, Sybase Adaptive Server, and PostgreSQL.Put the power and flexibility of SQL to work. With "Learning SQL" you can master this important skill and know that the SQL statements you write are indeed correct.

    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

    We'll use the world's most popular functional programming language: JavaScript. Some may feel this is a poor choice as it's against the grain of the current culture which, at the moment, feels predominately imperative. However, I believe it is the best way to learn FP for several reasons:You likely use it every day at work.This makes it possible to practice and apply your acquired knowledge each day on real world programs rather than pet projects on nights and weekends in an esoteric FP language.We don't have to learn everything up front to start writing programs.In a pure functional language, you cannot log a variable or read a DOM node without using monads. Here we can cheat a little as we learn to purify our codebase. It's also easier to get started in this language since it's mixed paradigm and you can fall back on your current practices while there are gaps in your knowledge.The language is fully capable of writing top notch functional code.We have all the features we need to mimic a language like Scala or Haskell with the help of a tiny library or two. Object-oriented programming currently dominates the industry, but it's clearly awkward in JavaScript. It's akin to camping off of a highway or tap dancing in galoshes. We have to bind all over the place lest this change out from under us, we don't have classes[^Yet], we have various work arounds for the quirky behavior when the new keyword is forgotten, private members are only available via closures. To a lot of us, FP feels more natural anyways.That said, typed functional languages will, without a doubt, be the best place to code in the style presented by this book. JavaScript will be our means of learning a paradigm, where you apply it is up to you. Luckily, the interfaces are mathematical and, as such, ubiquitous. You'll find yourself at home with swiftz, scalaz, haskell, purescript, and other mathematically inclined environments.

    Haskell emerged in the last decade as a standard for lazy functional programming, a programming style where arguments are evaluated only when the value is actually needed. Haskell is a marvellous demonstration tool for logic and maths because its functional character allows implementations to remain very close to the concepts that get implemented, while the laziness permits smooth handling of infinite data structures.This book does not assume the reader to have previous experience with either programming or construction of formal proofs, but acquaintance with mathematical notation, at the level of secondary school mathematics is presumed. Everything one needs to know about mathematical reasoning or programming is explained as we go along. After proper digestion of the material in this book the reader will be able to write interesting programs, reason about their correctness, and document them in a clear fashion. The reader will also have learned how to set up mathematical proofs in a structured way, and how to read and digest mathematical proofs written by others.

    Today, Rails developers and architects need better ways to interface with legacy systems, move into the cloud, and scale to handle higher volumes and greater complexity. In Service-Oriented Design with Ruby and Rails Paul Dix introduces a powerful, services-based design approach geared toward overcoming all these challenges. Using Dix's techniques, readers can leverage the full benefits of both Ruby and Rails, while overcoming the difficulties of working with larger codebases and teams. Dix demonstrates how to integrate multiple components within an enterprise application stack; create services that can easily grow and connect; and design systems that are easier to maintain and upgrade. Key concepts are explained with detailed Ruby code built using open source libraries such as ActiveRecord, Sinatra, Nokogiri, and Typhoeus. The book concludes with coverage of security, scaling, messaging, and interfacing with third-party services. Service-Oriented Design with Ruby and Rails will help you Build highly scalable, Ruby-based service architectures that operate smoothly in the cloud or with legacy systems Scale Rails systems to handle more requests, larger development teams, and more complex code bases Master new best practices for designing and creating services in Ruby Use Ruby to glue together services written in any language Use Ruby libraries to build and consume RESTful Web services Use Ruby JSON parsers to quickly represent resources from HTTP services Write lightweight, well-designed API wrappers around internal or external services Discover powerful non-Rails frameworks that simplify Ruby service implementation Implement standards-based enterprise messaging with Advanced Message Queuing Protocol (AMQP) Optimize performance with load balancing and caching Provide for security and authentication

    Dobbs Jolt Award Finalist since Bruce Schneier's Secrets and Lies and Applied Cryptography!Adam Shostack is responsible for security development lifecycle threat modeling at Microsoft and is one of a handful of threat modeling experts in the world. Now, he is sharing his considerable expertise into this unique book. With pages of specific actionable advice, he details how to build better security into the design of systems, software, or services from the outset. You'll explore various threat modeling approaches, find out how to test your designs against threats, and learn effective ways to address threats that have been validated at Microsoft and other top companies.Systems security managers, you'll find tools and a framework for structured thinking about what can go wrong. Software developers, you'll appreciate the jargon-free and accessible introduction to this essential skill. Security professionals, you'll learn to discern changing threats and discover the easiest ways to adopt a structured approach to threat modeling.Provides a unique how-to for security and software developers who need to design secure products and systems and test their designs Explains how to threat model and explores various threat modeling approaches, such as asset-centric, attacker-centric and software-centric Provides effective approaches and techniques that have been proven at Microsoft and elsewhere Offers actionable how-to advice not tied to any specific software, operating system, or programming language Authored by a Microsoft professional who is one of the most prominent threat modeling experts in the world As more software is delivered on the Internet or operates on Internet-connected devices, the design of secure software is absolutely critical. Make sure you're ready with Threat Modeling: Designing for Security.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    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.

    Delving into the history, philosophy, and even politics of object-oriented programming, West reveals how the best programmers rely on analysis and conceptualization on thinking rather than formal process and methods. Both provocative and pragmatic, this book gives form to what s primarily been an oral tradition among the field s revolutionary thinkers and it illustrates specific object-behavior practices that you can adopt for true object design and superior results.Gain an in-depth understanding of: Prerequisites and principles of object thinking. Object knowledge implicit in eXtreme Programming (XP) and Agile software development. Object conceptualization and modeling. Metaphors, vocabulary, and design for object development.Learn viable techniques for: Decomposing complex domains in terms of objects. Identifying object relationships, interactions, and constraints. Relating object behavior to internal structure and implementation design. Incorporating object thinking into XP and Agile practice."

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    The book is broken into two parts, the first deals with security-related reverse engineering and the second explores the more practical aspects of reverse engineering. In addition, the author explains how to reverse engineer a third-party software library to improve interfacing and how to reverse engineer a competitor's software to build a better product. * The first popular book to show how software reverse engineering can help defend against security threats, speed up development, and unlock the secrets of competitive products * Helps developers plug security holes by demonstrating how hackers exploit reverse engineering techniques to crack copy-protection schemes and identify software targets for viruses and other malware * Offers a primer on advanced reverse-engineering, delving into disassembly-code-level reverse engineering-and explaining how to decipher assembly language