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.

     Rails(TM) AntiPatterns identifies these widespread Rails code and design problems, explains why they're bad and why they happen--and shows exactly what to do instead.The book is organized into concise, modular chapters--each outlines a single common AntiPattern and offers detailed, cookbook-style code solutions that were previously difficult or impossible to find. Leading Rails developers Chad Pytel and Tammer Saleh also offer specific guidance for refactoring existing bad code or design to reflect sound object-oriented principles and established Rails best practices. With their help, developers, architects, and testers can dramatically improve new and existing applications, avoid future problems, and establish superior Rails coding standards throughout their organizations.This book will help you understand, avoid, and solve problems withModel layer code, from general object-oriented programming violations to complex SQL and excessive redundancy Domain modeling, including schema and database issues such as normalization and serialization View layer tools and conventions Controller-layer code, including RESTful code Service-related APIs, including timeouts, exceptions, backgrounding, and response codes Third-party code, including plug-ins and gems Testing, from test suites to test-driven development processes Scaling and deployment Database issues, including migrations and validations System design for "graceful degradation" in the real world

    Learn about the components of a BI architecture, how to choose the appropriate tools and technologies, and how to roll out a BI strategy throughout the organisation.

    But with a typical price tag of $5,000 to $10,000 for a usability consultant to conduct each round of tests, it rarely happens. In this how-to companion to Don't Make Me Think: A Common Sense Approach to Web Usability, Steve Krug spells out an approach to usability testing that anyone can easily apply to their own web site, application, or other product. (As he said in Don't Make Me Think, "It's not rocket surgery".)In this new book, Steve explains how to: -Test any design, from a sketch on a napkin to a fully-functioning web site or application-Keep your focus on finding the most important problems (because no one has the time or resources to fix them all)-Fix the problems that you find, using his "The least you can do" approachBy pairing the process of testing and fixing products down to its essentials (A morning a month, that's all we ask ), Rocket Surgery makes it realistic for teams to test early and often, catching problems while it's still easy to fix them. Rocket Surgery Made Easy adds demonstration videos to the proven mix of clear writing, before-and-after examples, witty illustrations, and practical advice that made Don't Make Me Think so popular.

    It also covers MySQL, and PostgreSQL. It contains examples which have been tested against each SQL platform, with incompatibilities or platform distinctives called out and explained.

    The twelve-factor app is a methodology for building software-as-a-service apps that: - Use declarative formats for setup automation, to minimize time and cost for new developers joining the project; - Have a clean contract with the underlying operating system, offering maximum portability between execution environments; - Are suitable for deployment on modern cloud platforms, obviating the need for servers and systems administration; - Minimize divergence between development and production, enabling continuous deployment for maximum agility; - And can scale up without significant changes to tooling, architecture, or development practices.The twelve-factor methodology can be applied to apps written in any programming language, and which use any combination of backing services (database, queue, memory cache, etc).

    

    In this one-of-a-kind text, author V. Anton Spraul breaks down the ways that programmers solve problems and teaches you what other introductory books often ignore: how to Think Like a Programmer. Each chapter tackles a single programming concept, like classes, pointers, and recursion, and open-ended exercises throughout challenge you to apply your knowledge. You'll also learn how to:Split problems into discrete components to make them easier to solve Make the most of code reuse with functions, classes, and libraries Pick the perfect data structure for a particular job Master more advanced programming tools like recursion and dynamic memory Organize your thoughts and develop strategies to tackle particular types of problems Although the book's examples are written in C++, the creative problem-solving concepts they illustrate go beyond any particular language; in fact, they often reach outside the realm of computer science. As the most skillful programmers know, writing great code is a creative art—and the first step in creating your masterpiece is learning to Think Like a Programmer.

    The authors also include examples covering a variety of different integration technologies, such as JMS, MSMQ, TIBCO ActiveEnterprise, Microsoft BizTalk, SOAP, and XSL. A case study describing a bond trading system illustrates the patterns in practice, and the book offers a look at emerging standards, as well as insights into what the future of enterprise integration might hold. This book provides a consistent vocabulary and visual notation framework to describe large-scale integration solutions across many technologies. It also explores in detail the advantages and limitations of asynchronous messaging architectures. The authors present practical advice on designing code that connects an application to a messaging system, and provide extensive information to help you determine when to send a message, how to route it to the proper destination, and how to monitor the health of a messaging system. If you want to know how to manage, monitor, and maintain a messaging system once it is in use, get this book.

     -Byte, September 1995 I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me! I have pored over them in cars, restaurants, at work, at home... and even at a Little League game when my son wasn't in the line-up. -Charles Long If you think you're a really good programmer... read [Knuth's] Art of Computer Programming... You should definitely send me a resume if you can read the whole thing. -Bill Gates It's always a pleasure when a problem is hard enough that you have to get the Knuths off the shelf. I find that merely opening one has a very useful terrorizing effect on computers. -Jonathan Laventhol This first volume in the series begins with basic programming concepts and techniques, then focuses more particularly on information structures-the representation of information inside a computer, the structural relationships between data elements and how to deal with them efficiently. Elementary applications are given to simulation, numerical methods, symbolic computing, software and system design. Dozens of simple and important algorithms and techniques have been added to those of the previous edition. The section on mathematical preliminaries has been extensively revised to match present trends in research. Ebook (PDF version) produced by Mathematical Sciences Publishers (MSP), http: //msp.org

    This brand new book from Ross Morrison McGill, bestselling author of 100 Ideas for Secondary Teachers: Outstanding Lessons and Teacher Toolkit, is packed full of practical ideas that will help teachers refine the key elements of their profession. Mark. Plan. Teach. shows how each stage of the teaching process informs the next, building a cyclical framework that underpins everything that teachers do.With teachers' workload at record levels and teacher recruitment and retention the number one issue in education, ideas that really work and will help teachers not only survive but thrive in the classroom are in demand. Every idea in Mark. Plan. Teach. can be implemented by all primary and secondary teachers at any stage of their career and will genuinely improve practice. The ideas have been tried and tested and are supported by evidence that explains why they work, including current educational research and psychological insights from Dr Tim O'Brien, leading psychologist and Visiting Fellow at UCL Institute of Education.Mark. Plan. Teach. will enable all teachers to maximise the impact of their teaching and, in doing so, save time, reduce workload and take back control of the classroom.

    Learn critical lessons from a person who helped design and build one of the largest high-performance .NET systems in the world.This book does not just teach you how the CLR works—it teaches you exactly what you need to do now to obtain the best performance today. It will expertly guide you through the nuts and bolts of extreme performance optimization in .NET, complete with in-depth examinations of CLR functionality, free tool recommendations and tutorials, useful anecdotes, and step-by-step guides to measure and improve performance.Among the topics you will learn are how to:-Choose what to measure and why-Use many amazing tools, freely available, to solve problems quickly-Understand the .NET garbage collector and its effect on your application-Use effective coding patterns that lead to optimal garbage collection performance-Diagnose common GC-related issues-Reduce costs of JITting-Use multiple threads sanely and effectively, avoiding synchronization problems-Know which .NET features and APIs to use and which to avoid-Use code generation to avoid performance problems-Measure everything and expose hidden performance issues-Instrument your program with performance counters and ETW events-Use the latest and greatest .NET features-Ensure your code can run on mobile devices without problems-Build a performance-minded team…and much more.

    

    With the same insight and authority that made their book The Unix programming Environment a classic, Brian Kernighan and Rob Pike have written The Practice of Programming to help make individual programmers more effective and productive.

    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