It is also about Python. However, there is much more. The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter. The only way to be successful is through deliberate and incremental exposure to the fundamental ideas. A beginning computer scientist needs practice so that there is a thorough understanding before continuing on to the more complex parts of the curriculum. In addition, a beginner needs to be given the opportunity to be successful and gain confidence. This textbook is designed to serve as a text for a first course on data structures and algorithms, typically taught as the second course in the computer science curriculum. Even though the second course is considered more advanced than the first course, this book assumes you are beginners at this level. You may still be struggling with some of the basic ideas and skills from a first computer science course and yet be ready to further explore the discipline and continue to practice problem solving. We cover abstract data types and data structures, writing algorithms, and solving problems. We look at a number of data structures and solve classic problems that arise. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

    His walk through the syntax and semantics of JavaScript is both charming and hugely insightful; reminders of gotchas complement realistic use cases, paced at a comfortable curve. You'll find when you finish the book that you've gained a strong and comprehensive sense of mastery." --Paul Irish, developer advocate, Google Chrome "This is not a book for those looking for shortcuts; rather it is hard-won experience distilled into a guided tour. It's one of the few books on JS that I'll recommend without hesitation." --Alex Russell, TC39 member, software engineer, Google In order to truly master JavaScript, you need to learn how to work effectively with the language's flexible, expressive features and how to avoid its pitfalls. No matter how long you've been writing JavaScript code, Effective JavaScript will help deepen your understanding of this powerful language, so you can build more predictable, reliable, and maintainable programs. Author David Herman, with his years of experience on Ecma's JavaScript standardization committee, illuminates the language's inner workings as never before--helping you take full advantage of JavaScript's expressiveness. Reflecting the latest versions of the JavaScript standard, the book offers well-proven techniques and best practices you'll rely on for years to come. Effective JavaScript is organized around 68 proven approaches for writing better JavaScript, backed by concrete examples. You'll learn how to choose the right programming style for each project, manage unanticipated problems, and work more successfully with every facet of JavaScript programming from data structures to concurrency. Key features include Better ways to use prototype-based object-oriented programming Subtleties and solutions for working with arrays and dictionary objects Precise and practical explanations of JavaScript's functions and variable scoping semantics Useful JavaScript programming patterns and idioms, such as options objects and method chaining In-depth guidance on using JavaScript's unique "run-to-completion" approach to concurrency

    On the other hand, if you're not well versed in the theory, you can fall into several traps. In SQL and Relational Theory, author C.J. Date demonstrates how you can apply relational theory directly to your use of SQL. With numerous examples and clear explanations of the reasoning behind them, you'll learn how to deal with common SQL dilemmas, such as:Should database access granted be through views instead of base tables? Nulls in your database are causing you to get wrong answers. Why? What can you do about it? Could you write an SQL query to find employees who have never been in the same department for more than six months at a time? SQL supports "quantified comparisons," but they're better avoided. Why? How do you avoid them? Constraints are crucially important, but most SQL products don't support them properly. What can you do to resolve this situation? Database theory and practice have evolved since Edgar Codd originally defined the relational model back in 1969. Independent of any SQL products, SQL and Relational Theory draws on decades of research to present the most up-to-date treatment of the material available anywhere. Anyone with a modest to advanced background in SQL will benefit from the many insights in this book.

    This practical guide from renowned software architect Neal Ford helps you transition from a Java-writing imperative programmer to a functional programmer, using Java, Clojure, and Scala as examples.Rather than focus on specific language features, Functional Thinking looks at a variety of common practices in OOP languages and then shows you how to solve the same problems with a functional language. For instance, you know how to achieve code-reuse in Java via mechanisms such as inheritance and polymorphism. Code reuse is also possible in functional languages, using high-order functions, composition, and multi-methods.Ford encourages you to value results over steps, so you can begin to think like a functional programmer. Expect your mind to be bent, but you’ll finish with a much better understanding of both the syntax and semantics of functional languages.

    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

    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.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    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.

    

    Richard Stevens' classic TCP/IP Illustrated, Volume 1 to gain the detailed understanding of TCP/IP they need to be effective. Now, the world's leading TCP/IP best-seller has been thoroughly updated to reflect a new generation of TCP/IP-based networking technologies. TCP/IP Illustrated, Volume 1, Second Edition doesn't just describe protocols: it enables readers to observe how these protocols operate under different conditions, using publicly available tools, and explains why key design decisions were made. The result: readers gain a deep understanding of how TCP/IP protocols function, and why they function that way. Now thoroughly updated by long-time networking expert Kevin Fall, this brand-new second edition's extensive new coverage includes: " Remote procedure call " Identity management (access control / authentication) " Network and transport layer security (authentication / privacy) " File access protocols, including NFS and SMB/CIFS " Host initialization and DHCP " NAT and firewalls " E-mail " Web and web services " Wireless and wireless security " New tools, including Ethereal, nmap and netcat

    With "React: Up and Running" you'll learn how to get off the ground with React, with no prior knowledge.This book teaches you how to build components, the building blocks of your apps, as well as how to organize the components into large-scale apps. In addition, you ll learn about unit testing and optimizing performance, while focusing on the application s data (and letting the UI take care of itself)."

    Concurrency and parallelism are the keys, and Seven Concurrency Models in Seven Weeks equips you for this new world. See how emerging technologies such as actors and functional programming address issues with traditional threads and locks development. Learn how to exploit the parallelism in your computer's GPU and leverage clusters of machines with MapReduce and Stream Processing. And do it all with the confidence that comes from using tools that help you write crystal clear, high-quality code. This book will show you how to exploit different parallel architectures to improve your code's performance, scalability, and resilience. Learn about the perils of traditional threads and locks programming and how to overcome them through careful design and by working with the standard library. See how actors enable software running on geographically distributed computers to collaborate, handle failure, and create systems that stay up 24/7/365. Understand why shared mutable state is the enemy of robust concurrent code, and see how functional programming together with technologies such as Software Transactional Memory (STM) and automatic parallelism help you tame it. You'll learn about the untapped potential within every GPU and how GPGPU software can unleash it. You'll see how to use MapReduce to harness massive clusters to solve previously intractible problems, and how, in concert with Stream Processing, big data can be tamed. With an understanding of the strengths and weaknesses of each of the different models and hardware architectures, you'll be empowered to tackle any problem with confidence.What You Need: The example code can be compiled and executed on *nix, OS X, or Windows. Instructions on how to download the supporting build systems are given in each chapter.

    Legendary testing expert James Whittaker, until recently a Google testing leader, and two top Google experts reveal exactly how Google tests software, offering brand-new best practices you can use even if you're not quite Google's size...yet! Breakthrough Techniques You Can Actually Use Discover 100% practical, amazingly scalable techniques for analyzing risk and planning tests...thinking like real users...implementing exploratory, black box, white box, and acceptance testing...getting usable feedback...tracking issues...choosing and creating tools...testing "Docs & Mocks," interfaces, classes, modules, libraries, binaries, services, and infrastructure...reviewing code and refactoring...using test hooks, presubmit scripts, queues, continuous builds, and more. With these techniques, you can transform testing from a bottleneck into an accelerator-and make your whole organization more productive!

    It includes detailed examples and exercises.

    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.