Readers will progress from building a basic physics engine to creating intelligent moving objects and complex systems, setting the foundation for further experiments in generative design. Subjects covered include forces, trigonometry, fractals, cellular automata, self-organization, and genetic algorithms. The book's examples are written in Processing, an open-source language and development environment built on top of the Java programming language. On the book's website (http://www.natureofcode.com), the examples run in the browser via Processing's JavaScript mode.

    "This book is a guide to how we do product development at Basecamp. It’s also a toolbox full of techniques that you can apply in your own way to your own process.Whether you’re a founder, CTO, product manager, designer, or developer, you’re probably here because of some common challenges that all software companies have to face."

    This is why it is imperative to build systems that are flexible and can adapt to changing requirements, both expected and (more often) unexpected. That is why I've written this book.From 2009 to 2014, I traveled the world working with software developers, both individually and in teams, to improve their craft. Primarily, I did this through a training workshop format called coderetreat. Over those years, I had the opportunity to watch 1000's of pairs of programmers work on exactly the same system, Conway's Game of Life. As time progressed, I began to see patterns arise. I noticed common techniques and designs that spanned languages and companies and crossed national borders.As co-founder and a facilitator of coderetreat workshops, I had the unique opportunity to provide feedback, both direct and through questions, on improving the act of writing adaptable, simple code. Through the day, we worked on improving our ability to make good choices around the minute-by-minute decisions made while writing code.This book is about those things I learned from watching these 1000's of pairs working on the same problem. It contains a large part of the feedback that I provide during a typical coderetreat. The primary focus is on the thought process behind refactoring, and how that is influenced by the 4 rules of simple design.This book is not about Conway's Game of Life. Instead, it uses its domain as a backdrop to discuss the thoughts and ideas behind the 4 rules of simple design. It focuses on the small decisions made while designing your code with the goal of building robust, adaptable codebases that can stand the test of time.

    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.

    Servers give sysadmins a incredible visibility into the network—once they know how to unlock it. Most sysadmins don’t need to understand window scaling, or the differences between IPv4 and IPv6 echo requests, or other intricacies of the TCP/IP protocols. You need only enough to deploy your own applications and get easy support from the network team.This book teaches you:•How modern networks really work•The essentials of TCP/IP•The next-generation protocol, IPv6•The right tools to diagnose network problems, and how to use them•Troubleshooting everything from the physical wire to DNS•How to see the traffic you send and receive•Connectivity testing•How to communicate with your network team to quickly resolve problemsA systems administrator doesn’t need to know the innards of TCP/IP, but knowing enough to diagnose your own network issues transforms a good sysadmin into a great one.

    Russ Olsen has done a great job of selecting classic patterns and augmenting these with newer patterns that have special relevance for Ruby. He clearly explains each idea, making a wealth of experience available to Ruby developers for their own daily work."--Steve Metsker, Managing Consultant with Dominion Digital, Inc."This book provides a great demonstration of the key 'Gang of Four' design patterns without resorting to overly technical explanations. Written in a precise, yet almost informal style, this book covers enough ground that even those without prior exposure to design patterns will soon feel confident applying them using Ruby. Olsen has done a great job to make a book about a classically 'dry' subject into such an engaging and even occasionally humorous read."--Peter Cooper"This book renewed my interest in understanding patterns after a decade of good intentions. Russ picked the most useful patterns for Ruby and introduced them in a straightforward and logical manner, going beyond the GoF's patterns. This book has improved my use of Ruby, and encouraged me to blow off the dust covering the GoF book."--Mike Stok" Design Patterns in Ruby is a great way for programmers from statically typed objectoriented languages to learn how design patterns appear in a more dynamic, flexible language like Ruby."--Rob Sanheim, Ruby Ninja, RelevanceMost design pattern books are based on C++ and Java. But Ruby is different--and the language's unique qualities make design patterns easier to implement and use. In this book, Russ Olsen demonstrates how to combine Ruby's power and elegance with patterns, and write more sophisticated, effective software with far fewer lines of code.After reviewing the history, concepts, and goals of design patterns, Olsen offers a quick tour of the Ruby language--enough to allow any experienced software developer to immediately utilize patterns with Ruby. The book especially calls attention to Ruby features that simplify the use of patterns, including dynamic typing, code closures, and "mixins" for easier code reuse.Fourteen of the classic "Gang of Four" patterns are considered from the Ruby point of view, explaining what problems each pattern solves, discussing whether traditional implementations make sense in the Ruby environment, and introducing Ruby-specific improvements. You'll discover opportunities to implement patterns in just one or two lines of code, instead of the endlessly repeated boilerplate that conventional languages often require. Design Patterns in Ruby also identifies innovative new patterns that have emerged from the Ruby community. These include ways to create custom objects with metaprogramming, as well as the ambitious Rails-based "Convention Over Configuration" pattern, designed to help integrate entire applications and frameworks.Engaging, practical, and accessible, Design Patterns in Ruby will help you build better software while making your Ruby programming experience more rewarding.

    In this friendly, pragmatic book, cloud experts John Arundel and Justin Domingus show you what Kubernetes can do--and what you can do with it.You'll learn all about the Kubernetes ecosystem, and use battle-tested solutions to everyday problems. You'll build, step by step, an example cloud native application and its supporting infrastructure, along with a development environment and continuous deployment pipeline that you can use for your own applications.Understand containers and Kubernetes from first principles; no experience necessaryRun your own clusters or choose a managed Kubernetes service from Amazon, Google, and othersUse Kubernetes to manage resource usage and the container lifecycleOptimize clusters for cost, performance, resilience, capacity, and scalabilityLearn the best tools for developing, testing, and deploying your applicationsApply the latest industry practices for security, observability, and monitoringAdopt DevOps principles to help make your development teams lean, fast, and effective

    As expected, .NET 4 brings a wealth of new APIs to the base class libraries and several new syntactical constructs to C#. For example, it is now possible to create C# methods that support optional and named arguments. As well, you are able to resolve types completely at runtime using the new dynamic keyword. As far as APIs are concerned, this edition of Pro C# 2010 and the .NET 4 Platform will cover a number of new details, including:• the Dynamic Language Runtime (DLR)• the Task Parallel Library (TPL, including PLINQ)• the ADO.NET Entity Framework (as well as LINQ to EF)• expanded coverage of the Windows Presentation Foundation (WPF) API• improved support for COM interopIf you're checking out this book for the first time, understand that it targets experienced software professionals and students of computer science—so please don't expect three chapters devoted to "variable scope" here! The mission of this text is to provide you with a rock-solid foundation in the C# programming language (including a full discussion of OOP) and the critical aspects of the .NET 4 platform.Once you digest the information presented in the book you hold in your hands, you'll be in a perfect position to apply this knowledge to your specific programming assignments, and you'll be well-equipped to explore the .NET universe on your own terms.Andrew TroelsenMicrosoft MVP, Visual Developer—Visual C#; Microsoft Certified Trainer (MCT)

    Written from a computer science perspective by three leading experts in the field, it gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Although originally designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also create a buzz for researchers and professionals alike.

    Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center.Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel, it is a joy to read. Tim Roughgarden Stanford University

    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.

    And I mean all the time. Every day there’s a new cloud-based dating app; a new cloud-based gizmo for your house; a new cloud-based game; or a thousand other new things—all in the cloud.The cloud is everywhere! Everything is in the cloud! What does it mean! Let’s slow down. Take a deep breath. That’s good. Take another. Excellent. This book teaches you all about the cloud. I’ll let you in on a little secret: the cloud is not that hard to understand. It’s not. It’s just that nobody has taken the time to explain to you what the cloud is. They haven’t, have they?Deep down I think this is because they don’t understand the cloud either, but I do. I’ve been a programmer and writer for over 30 years. I’ve been in cloud computing since the very start, and I’m here to help you on your journey to understand the cloud. Consider me your tour guide. I’ll be with you every step of the way, but not in a creepy way.I take my time with this book. I go slow and easy, so you can build up an intuition about what the cloud really is, one idea at a time. When you finish reading, you’ll understand the cloud. When you hear someone say some new cool thing is in the cloud, you’ll understand exactly what they mean. That’s a promise. How do I deliver on that promise? I use lots and lots of pictures. I use lots and lots of examples. We’ll reveal the secret inner-workings of AWS, Netflix, Facebook Messenger, Amazon Kindle, Apple iCloud, Google Maps, Nest and cloud DVRs. You’ll learn by seeing and understanding; no matter if you're a complete beginner, someone who knows a little and wants to learn more, or a programmer looking to change their career to the cloud.The cloud is the future. You don't want to miss out on the future, do you? Read this book and we'll discover it together.I’m excited. This will be fun. Let’s get started!

    But which claims are verifiable, and which are merely wishful thinking? In this book, leading thinkers such as Steve McConnell, Barry Boehm, and Barbara Kitchenham offer essays that uncover the truth and unmask myths commonly held among the software development community. Their insights may surprise you.Are some programmers really ten times more productive than others?Does writing tests first help you develop better code faster?Can code metrics predict the number of bugs in a piece of software?Do design patterns actually make better software?What effect does personality have on pair programming?What matters more: how far apart people are geographically, or how far apart they are in the org chart?Contributors include:Jorge Aranda Tom Ball Victor R. Basili Andrew Begel Christian Bird Barry Boehm Marcelo Cataldo Steven Clarke Jason Cohen Robert DeLine Madeline Diep Hakan Erdogmus Michael Godfrey Mark Guzdial Jo E. Hannay Ahmed E. Hassan Israel Herraiz Kim Sebastian Herzig Cory Kapser Barbara Kitchenham Andrew Ko Lucas Layman Steve McConnell Tim Menzies Gail Murphy Nachi Nagappan Thomas J. Ostrand Dewayne Perry Marian Petre Lutz Prechelt Rahul Premraj Forrest Shull Beth Simon Diomidis Spinellis Neil Thomas Walter Tichy Burak Turhan Elaine J. Weyuker Michele A. Whitecraft Laurie Williams Wendy M. Williams Andreas Zeller Thomas Zimmermann

    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

    And it’s still short, profusely illustrated…and best of all–fun to read.If you’ve read it before, you’ll rediscover what made Don’t Make Me Think so essential to Web designers and developers around the world. If you’ve never read it, you’ll see why so many people have said it should be required reading for anyone working on Web sites.