We'll introduce you to various tips, tricks, patterns, code snippets, and techniques that we've picked up over the years.This book is great for:Beginners who have just finished the Django tutorial.Developers with intermediate knowledge of Django who want to improve their Django projects.

    "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    Until now. This practical guide provides the first comprehensive overview of software architecture's many aspects. You'll examine architectural characteristics, architectural patterns, component determination, diagramming and presenting architecture, evolutionary architecture, and many other topics.Authors Neal Ford and Mark Richards help you learn through examples in a variety of popular programming languages, such as Java, C#, JavaScript, and others. You'll focus on architecture principles with examples that apply across all technology stacks.

    This book uses the common sense of these roads and weaves it into the implementation of an attractive app. You will build a Hacker News React app. On the road you will learn ES6, React with all its basics and advanced concepts and internal state management.' to 'A lot of roadmaps exist on how to master React. This book uses the common sense of these roads and weaves it into the implementation of an attractive app. You will build a Hacker News React app. On the road you will learn ES6, React with all its basics and advanced concepts and internal state management. http://www.robinwieruch.de/the-road-t...

    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.

    It has become popular in recent years because of its simplicity, conciseness, and clarity. This book teaches functional programming as a way of thinking and problem solving, using Haskell, the most popular purely functional language. Rather than using the conventional (boring) mathematical examples commonly found in other programming language textbooks, the author uses examples drawn from multimedia applications, including graphics, animation, and computer music, thus rewarding the reader with working programs for inherently more interesting applications. Aimed at both beginning and advanced programmers, this tutorial begins with a gentle introduction to functional programming and moves rapidly on to more advanced topics. Details about progamming in Haskell are presented in boxes throughout the text so they can be easily found and referred to.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    But testing is not a routine process, it's a constant exploration of methods and an evolution of good ideas.Beautiful Testing offers 23 essays from 27 leading testers and developers that illustrate the qualities and techniques that make testing an art. Through personal anecdotes, you'll learn how each of these professionals developed beautiful ways of testing a wide range of products -- valuable knowledge that you can apply to your own projects. Here's a sample of what you'll find inside:Microsoft's Alan Page shares some of his secrets about large-scale test automation.Scott Barber explains why performance testing needs to be a collaborative process, rather than simply an exercise in measuring speed.Karen Johnson describes how her professional experience intersected her personal life while testing medical software.Rex Black reveals how satisfying stakeholders for 25 years is a beautiful thingMathematician John D. Cook applies a classic definition of beauty, based on complexity and unity, to testing random number generatorsAll author royalties will be donated to the Nothing But Nets campaign to save lives by preventing malaria, a disease that kills millions of children in Africa each year.ContentsI. BEAUTIFUL TESTERS 1. Was it good for you? (Linda Wilkinson)2. Beautiful testing satisfies stakeholders (Rex Black)3. Building open source QA communities (Martin Schröder, Clint Talbert)4. Collaboration is the cornerstone of beautiful performance testing (Scott Barber)II. BEAUTIFUL PROCESS5. Just peachy: Making office software more reliable with fuzz testing (Kamran Khan)6. Bug management and test case effectiveness (Emily Chen, Brian Nitz)7. Beautiful XMPP Testing (Remko Troncon)8. Beautiful large-scale test automation (Alan Page)9. Beautiful is better than ugly (Neal Norwitz, Michelle Levesque, Jeffrey Yaskin)10. Testing a random number generator (John D. Cook)11. Change-centric testing (Murali Nandigama)12. Software in use (Karen N. Johnson)13. Software development is a creative process (Chris McMahon)14. Test-driven development: Driving new standards of beauty (Jennitta Andrea)15. Beautiful testing as the cornerstone of business success (Lisa Crispin)16. Peeling the glass onion at Socialtext (Mathew Heusser)17. Beautiful testing is efficient testing (Adam Goucher)III. BEAUTIFUL TOOLS18. Seeding bugs to find bugs: Beautiful mutation testing (Andreas Zeller, David Schuler)19. Reference testing as beautiful testing (Clint Talbert)20. CLAM Anti-virus: testing open source with open tools (Tomasz Kojm)21. Web application testing with Windmill (Adam Christian)22. Testing one million web pages (Tim Riley)23. Testing Network Services in Multimachine Scenarios (Isaac Clerencia)ContributorsIndex

    The biggest change comes in the growing prominence and acceptance of Agile Programming. Software Testing—A Craftsman’s Approach, Third Edition extends the combination of theory and practicality of the first two editions to include agile programming development and discusses the serious effect this emerging area is having on software testing. Extend your Knowledge of Emerging Technologies The third edition of the widely adopted text and reference book is comprised of six parts. It begins by providing the mathematical background in discrete mathematics and linear graph theory that is used in subsequent sections. The book continues to describe specification-based (functional) and code-based (structural) test development techniques, while extending this theoretical approach to less understood levels of integration and system testing. The author further develops this discussion to include object-oriented software. A completely new section relates all of the previously discussed concepts to the agile software development movement and highlights issues such as how agile and XP development environments are radically changing the role of software testers by making testing integral at every phase of the development process. Thoroughly revised and updated, Software Testing—A Craftsman’s Approach , Third Edition is sure to become a standard reference for those who need to stay up-to-date on the most recent technologies in software testing. Carrying on the tradition of previous editions, it will continue to serve as a valuable reference for software testers, developers, and engineers. Table Of Contents: PART I: A MATHEMATICAL CONTEXT A Perspective on Testing Basic Definitions Test Cases Insights from a Venn Diagram Identifying Test Cases Error and Fault Taxonomies Levels of Testing Examples Generalized Pseud

    Networking All-in-One For Dummies, 4th Edition is like ten books in one, covering such topics as networking basics, network security, setting up TCP/IP and connecting to the Internet, handling mobile devices, and much more. This valuable book covers all the newest updates and trends, including Windows 7 and Windows Server 2008 R2.A single-source reference for network administrators Includes ten minibooks: Networking Basics; Building a Network; Network Administration and Security; TCP/IP and the Internet; Wireless Networking; Telecom, Convergence, and Mobile Devices; Windows Server 2008 Reference; Using Other Windows Servers; Linux Networking Reference; and Appendices Explores the latest technologies in broadband, storage, and back-up Delves into new trends in networking and includes the latest Windows Server 2008 R2 and Windows 7 updates System administrators will want to keep this practical all-in-one guide within reach.

    Getting started with this JavaScript library is easy, but it can take years to fully realize its breadth and depth; this cookbook shortens the learning curve considerably. With these recipes, you'll learn patterns and practices from 19 leading developers who use jQuery for everything from integrating simple components into websites and applications to developing complex, high-performance user interfaces. Ideal for newcomers and JavaScript veterans alike, jQuery Cookbook starts with the basics and then moves to practical use cases with tested solutions to common web development hurdles. You also get recipes on advanced topics, such as methods for applying jQuery to large projects.Solve problems involving events, effects, dimensions, forms, themes, and user interface elementsLearn how to enhance your forms, and how to position and reposition elements on a pageMake the most of jQuery's event management system, including custom events and custom event dataCreate UI elements-such as tabs, accordions, and modals-from scratchOptimize your code to eliminate bottlenecks and ensure peak performanceLearn how to test your jQuery applicationsThe book's contributors include:Cody LindleyJames PadolseyRalph WhitbeckJonathan SharpMichael Geary and Scott GonzálezRebecca MurpheyRemy SharpAriel FleslerBrian CherneJörn ZaeffererMike HostetlerNathan SmithRichard D. WorthMaggie Wachs, Scott Jehl, Todd Parker, and Patty TolandRob Burns

    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

    Often, computer science and computer engineering curricula don't provide students with a concentrated and consistent introduction to the fundamental concepts that underlie all computer systems. Traditional computer organization and logic design courses cover some of this material, but they focus largely on hardware design. They provide students with little or no understanding of how important software components operate, how application programs use systems, or how system attributes affect the performance and correctness of application programs. - A more complete view of systems - Takes a broader view of systems than traditional computer organization books, covering aspects of computer design, operating systems, compilers, and networking, provides students with the understanding of how programs run on real systems. - Systems presented from a programmers perspective - Material is presented in such a way that it has clear benefit to application programmers, students learn how to use this knowledge to improve program performance and reliability. They also become more effective in program debugging, because t

    Over the past five years, authors Dustin Boswell and Trevor Foucher have analyzed hundreds of examples of "bad code" (much of it their own) to determine why they’re bad and how they could be improved. Their conclusion? You need to write code that minimizes the time it would take someone else to understand it—even if that someone else is you.This book focuses on basic principles and practical techniques you can apply every time you write code. Using easy-to-digest code examples from different languages, each chapter dives into a different aspect of coding, and demonstrates how you can make your code easy to understand.Simplify naming, commenting, and formatting with tips that apply to every line of codeRefine your program’s loops, logic, and variables to reduce complexity and confusionAttack problems at the function level, such as reorganizing blocks of code to do one task at a timeWrite effective test code that is thorough and concise—as well as readable"Being aware of how the code you create affects those who look at it later is an important part of developing software. The authors did a great job in taking you through the different aspects of this challenge, explaining the details with instructive examples." —Michael Hunger, passionate Software Developer

    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.