If you're a reasonably proficient programmer who can think logically, you have all the background you'll need. Stepanov and Rose introduce the relevant abstract algebra and number theory with exceptional clarity. They carefully explain the problems mathematicians first needed to solve, and then show how these mathematical solutions translate to generic programming and the creation of more effective and elegant code. To demonstrate the crucial role these mathematical principles play in many modern applications, the authors show how to use these results and generalized algorithms to implement a real-world public-key cryptosystem. As you read this book, you'll master the thought processes necessary for effective programming and learn how to generalize narrowly conceived algorithms to widen their usefulness without losing efficiency. You'll also gain deep insight into the value of mathematics to programming--insight that will prove invaluable no matter what programming languages and paradigms you use. You will learn aboutHow to generalize a four thousand-year-old algorithm, demonstrating indispensable lessons about clarity and efficiencyAncient paradoxes, beautiful theorems, and the productive tension between continuous and discreteA simple algorithm for finding greatest common divisor (GCD) and modern abstractions that build on itPowerful mathematical approaches to abstractionHow abstract algebra provides the idea at the heart of generic programmingAxioms, proofs, theories, and models: using mathematical techniques to organize knowledge about your algorithms and data structuresSurprising subtleties of simple programming tasks and what you can learn from themHow practical implementations can exploit theoretical knowledge

    Though it may not seem this way for those who have been in the field for most of their careers, in the overall scheme of professions, software builders are relative "newbies." In the short history of the software field, a lot of facts have been identified, and a lot of fallacies promulgated. Those facts and fallacies are what this book is about. There's a problem with those facts-and, as you might imagine, those fallacies. Many of these fundamentally important facts are learned by a software engineer, but over the short lifespan of the software field, all too many of them have been forgotten. While reading Facts and Fallacies of Software Engineering , you may experience moments of "Oh, yes, I had forgotten that," alongside some "Is that really true?" thoughts. The author of this book doesn't shy away from controversy. In fact, each of the facts and fallacies is accompanied by a discussion of whatever controversy envelops it. You may find yourself agreeing with a lot of the facts and fallacies, yet emotionally disturbed by a few of them! Whether you agree or disagree, you will learn why the author has been called "the premier curmudgeon of software practice." These facts and fallacies are fundamental to the software building field-forget or neglect them at your peril!

     Coauthored by the designer of the Scala language, this authoritative book will teach you, one step at a time, the Scala language and the ideas behind it. The book is carefully crafted to help you learn. The first few chapters will give you enough of the basics that you can already start using Scala for simple tasks. The entire book is organized so that each new concept builds on concepts that came before - a series of steps that promises to help you master the Scala language and the important ideas about programming that Scala embodies. A comprehensive tutorial and reference for Scala, this book covers the entire language and important libraries.

    You'll quickly learn the language's fundamentals, then move onto persistence, exception handling, web development, SQLite, data wrangling, and Google App Engine. You'll also learn how to write mobile apps for Android, all thanks to the power that Python gives you.We think your time is too valuable to waste struggling with new concepts. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Python uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.

    Tech companies in general lack the experience, tools, texts, and frameworks to do it well. And the handful of books that share tips and tricks of engineering management don t explain how to supervise employees in the face of growth and change.In this book, author Camille Fournier takes you through the stages of technical management, from mentoring interns to working with the senior staff. You ll get actionable advice for approaching various obstacles in your path, whether you re a new manager, a mentor, or a more experienced leader looking for fresh advice. Pick up this book and learn how to become a better manager and leader in your organization. * Discover how to manage small teams and large/multi-level teams * Understand how to build and bootstrap a unifying culture in teams * Deal with people problems and learn how to mentor other managers and new leaders * Learn how to manage yourself: avoid common pitfalls that challenge many leaders * Obtain several practices that you can incorporate and practice along the way

    The book begins with the basic concepts of logic and set theory, to familiarize students with the language of mathematics and how it is interpreted. These concepts are used as the basis for a step-by-step breakdown of the most important techniques used in constructing proofs. To help students construct their own proofs, this new edition contains over 200 new exercises, selected solutions, and an introduction to Proof Designer software. No background beyond standard high school mathematics is assumed. Previous Edition Hb (1994) 0-521-44116-1 Previous Edition Pb (1994) 0-521-44663-5

    Cooper details many of these meta functions to explain his central thesis: programmers need to seriously re-evaluate the many user-hostile concepts deeply embedded within the software development process. Rather than provide users with a straightforward set of options, programmers often pile on the bells and whistles and ignore or de-prioritise lingering bugs. For the average user, increased functionality is a great burden, adding to the recurrent chorus that plays: "computers are hard, mysterious, unwieldy things." (An average user, Cooper asserts, who doesn't think that way or who has memorised all the esoteric commands and now lords it over others, has simply been desensitised by too many years of badly designed software.) Cooper's writing style is often overblown, with a pantheon of cutesy terminology (i.e. "dancing bearware") and insider back-patting. (When presenting software to Bill Gates, he reports that Gates replied: "How did you do that?" to which he writes: "I love stumping Bill!") More seriously, he is also unable to see beyond software development's importance--a sin he accuses programmers of throughout the book. Even with that in mind, the central questions Cooper asks are too important to ignore: Are we making users happier? Are we improving the process by which they get work done? Are we making their work hours more effective? Cooper looks to programmers, business managers and what he calls "interaction designers" to question current assumptions and mindsets. Plainly, he asserts that the goal of computer usage should be "not to make anyone feel stupid." Our distance from that goal reinforces the need to rethink entrenched priorities in software planning. -- Jennifer Buckendorff, Amazon.com

    This practical guide not only shows you how to search, analyze, and explore data with Elasticsearch, but also helps you deal with the complexities of human language, geolocation, and relationships.If you're a newcomer to both search and distributed systems, you'll quickly learn how to integrate Elasticsearch into your application. More experienced users will pick up lots of advanced techniques. Throughout the book, you'll follow a problem-based approach to learn why, when, and how to use Elasticsearch features.Understand how Elasticsearch interprets data in your documentsIndex and query your data to take advantage of search concepts such as relevance and word proximityHandle human language through the effective use of analyzers and queriesSummarize and group data to show overall trends, with aggregations and analyticsUse geo-points and geo-shapes--Elasticsearch's approaches to geolocationModel your data to take advantage of Elasticsearch's horizontal scalabilityLearn how to configure and monitor your cluster in production

    Published first in 1984, it could be among the timeless classics of computer books, such as Fred Brooks' The Mythical Man-Month and Donald Knuth's The Art of Computer Programming. Many software engineering principles discussed here have been rediscovered in eXtreme Programming, including (re)factoring, modularity, bottom-up and incremental design. Here you'll find all of those and more, such as the value of analysis and design, described in Leo Brodie's down-to-earth, humorous style, with illustrations, code examples, practical real life applications, illustrative cartoons, and interviews with Forth's inventor, Charles H. Moore as well as other Forth thinkers.

    It brings together all the knowledge needed to write any program, use any standard or third-party Python 3 library, and create new library modules of your own.

    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.

    In Turing’s Cathedral, George Dyson focuses on a small group of men and women, led by John von Neumann at the Institute for Advanced Study in Princeton, New Jersey, who built one of the first computers to realize Alan Turing’s vision of a Universal Machine. Their work would break the distinction between numbers that mean things and numbers that do things—and our universe would never be the same. Using five kilobytes of memory (the amount allocated to displaying the cursor on a computer desktop of today), they achieved unprecedented success in both weather prediction and nuclear weapons design, while tackling, in their spare time, problems ranging from the evolution of viruses to the evolution of stars. Dyson’s account, both historic and prophetic, sheds important new light on how the digital universe exploded in the aftermath of World War II. The proliferation of both codes and machines was paralleled by two historic developments: the decoding of self-replicating sequences in biology and the invention of the hydrogen bomb. It’s no coincidence that the most destructive and the most constructive of human inventions appeared at exactly the same time.  How did code take over the world? In retracing how Alan Turing’s one-dimensional model became John von Neumann’s two-dimensional implementation, Turing’s Cathedral offers a series of provocative suggestions as to where the digital universe, now fully three-dimensional, may be heading next.

    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.

    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)