It's used worldwide by companies who need to produce reliable, efficient, and scalable applications. Invest in learning Erlang now.Moore's Law is the observation that the amount you can do on a single chip doubles every two years. But Moore's Law is taking a detour. Rather than producing faster and faster processors, companies such as Intel and AMD are producing multi-core devices: single chips containing two, four, or more processors. If your programs aren't concurrent, they'll only run on a single processor at a time. Your users will think that your code is slow.Erlang is a programming language designed for building highly parallel, distributed, fault-tolerant systems. It has been used commercially for many years to build massive fault-tolerated systems that run for years with minimal failures.Erlang programs run seamlessly on multi-core computers: this means your Erlang program should run a lot faster on a 4 core processor than on a single core processor, all without you having to change a line of code.Erlang combines ideas from the world of functional programming with techniques for building fault-tolerant systems to make a powerful language for building the massively parallel, networked applications of the future.This book presents Erlang and functional programming in the familiar Pragmatic style. And it's written by Joe Armstrong, one of the creators of Erlang.It includes example code you'll be able to build upon. In addition, the book contains the full source code for two interesting applications:A SHOUTcast server which you can use to stream music to every computer in your house, and a full-text indexing and search engine that can index gigabytes of data. Learn how to write programs that run on dozens or even hundreds of local and remote processors. See how to write robust applications that run even in the face of network and hardware failure, using the Erlang programming language.

    Learn practical programming and best practices. Meet the difficult challenges of C++ development. Build reliable and robust programs. Design Patterns chapter shows sophisticated use of objects, composition and polymorphism. Provides a gentle introduction to multithreaded programming, a feature being considered for the next version of Standard C++. Defensive Programming chapter includes a simple unit-testing framework and debugging techniques. In-depth treatment of Standard C++ Library facilities including strings, iostreams, and the "STL" algorithms and containers. Modern usage of templates, including template metaprogramming. Unravels the perplexities of multiple inheritance. Shows practical uses for RTTI. Explores exception handling in depth and clearly explains exception-safe design. Compliant with the official ISO C++ Standard. Presents results of current research being considered for inclusion in the next revision of Standard C++. All code examples freely downloadable, tested on multiple platforms and compilers including the free GNU C++ compiler on Windows/Mac/Linux. On www.BruceEckel.com: Annotated Solutions Guide Seminars and consulting Free Download—Volume I of this book Annotation Thinking in C++ is ideal for anyone already familiar with C who now wants to learn C++. Eckel has synthesized more than five years of C++ teaching and programming experience into a well-structured course that moves step-by-step through each important C++ concept. He highlights poorly-understood C++ features like virtual functions, which can improve productivity. Editorial Reviews The Barnes & Noble Review Bruce Eckel, one of the world's best programming trainers, has thoroughly updated his classic THINKING IN C++—the book that won the Software Development Magazine Jolt Cola award in its first iteration. The new version is better than ever—which is to say, it's

    With IDA Pro, you live in a source code-optional world. IDA can automatically analyze the millions of opcodes that make up an executable and present you with a disassembly. But at that point, your work is just beginning. With The IDA Pro Book, you'll learn how to turn that mountain of mnemonics into something you can actually use.Hailed by the creator of IDA Pro as the "long-awaited" and "information-packed" guide to IDA, The IDA Pro Book covers everything from the very first steps to advanced automation techniques. While other disassemblers slow your analysis with inflexibility, IDA invites you to customize its output for improved readability and usefulness. You'll save time and effort as you learn to:Identify known library routines, so you can focus your analysis on other areas of the code Extend IDA to support new processors and filetypes, making disassembly possible for new or obscure architectures Explore popular plug-ins that make writing IDA scripts easier, allow collaborative reverse engineering, and much more Utilize IDA's built-in debugger to tackle obfuscated code that would defeat a stand-alone disassembler You'll still need serious assembly skills to tackle the toughest executables, but IDA makes things a lot easier. Whether you're analyzing the software on a black box or conducting hard-core vulnerability research, a mastery of IDA Pro is crucial to your success. Take your skills to the next level with The IDA Pro Book.

    It can be freely downloaded and it works on multiple computer platforms. This book provides an elementary introduction to R. In each chapter, brief introductory sections are followed by code examples and comments from the computational and statistical viewpoint. A supplementary R package containing the datasets can be downloaded from the web.

    With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems.Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution.Model data with the Cypher query language and property graph modelLearn best practices and common pitfalls when modeling with graphsPlan and implement a graph database solution in test-driven fashionExplore real-world examples to learn how and why organizations use a graph databaseUnderstand common patterns and components of graph database architectureUse analytical techniques and algorithms to mine graph database information

    It requires three to five times less time than developing in Java, is a great building block for learning both procedural and object-oriented programming concepts, and is an ideal language for data analysis. Beginning Programming with Python For Dummies is the perfect guide to this dynamic and powerful programming language--even if you've never coded before! Author John Paul Mueller draws on his vast programming knowledge and experience to guide you step-by-step through the syntax and logic of programming with Python and provides several real-world programming examples to give you hands-on experience trying out what you've learned.Provides a solid understanding of basic computer programming concepts and helps familiarize you with syntax and logic Explains the fundamentals of procedural and object-oriented programming Shows how Python is being used for data analysis and other applications Includes short, practical programming samples to apply your skills to real-world programming scenarios Whether you've never written a line of code or are just trying to pick up Python, there's nothing to fear with the fun and friendly Beginning Programming with Python For Dummies leading the way.

    Fundamentals of Data Structures in C++ offers a complete rendering of basic data structure implementations, enhanced by superior pedagogy and astute analyses.

    Jonathan Stark shows you how to leverage your existing web development skills to build native iPhone applications using these technologies." --John Allsopp, author and founder of Web Directions"Jonathan's book is the most comprehensive documentation available for developing web applications for mobile Safari. Not just great tech coverage, this book is an easy read of purely fascinating mobile tidbits in a fun colloquial style. Must have for all PhoneGap developers." -- Brian LeRoux, Nitobi SoftwareIt's a fact: if you know HTML, CSS, and JavaScript, you already have the tools you need to develop your own iPhone apps. With this book, you'll learn how to use these open source web technologies to design and build apps for the iPhone and iPod Touch on the platform of your choice-without using Objective-C or Cocoa.Device-agnostic mobile apps are the wave of the future, and this book shows you how to create one product for several platforms. You'll find guidelines for converting your product into a native iPhone app using the free PhoneGap framework. And you'll learn why releasing your product as a web app first helps you find, fix, and test bugs much faster than if you went straight to the App Store with a product built with Apple's tools.Build iPhone apps with tools you already know how to useLearn how to make an existing website look and behave like an iPhone appAdd native-looking animations to your web app using jQTouchTake advantage of client-side data storage with apps that run even when the iPhone is offlineHook into advanced iPhone features -- including the accelerometer, geolocation, and vibration -- with JavaScriptSubmit your applications to the App Store with XcodeThis book received valuable community input through O'Reilly's Open Feedback Publishing System (OFPS). Learn more at http://labs.oreilly.com/ofps.html.

    It takes a fairly traditional approach, emphasizing problem solving, design, and programming as the core skills of computer science. However, these ideas are illustrated using a non-traditional language, namely Python. Although I use Python as the language, teaching Python is not the main point of this book. Rather, Python is used to illustrate fundamental principles of design and programming that apply in any language or computing environment. In some places, I have purposely avoided certain Python features and idioms that are not generally found in other languages. There are already many good books about Python on the market; this book is intended as an introduction to computing. Features include the following: *Extensive use of computer graphics. *Interesting examples. *Readable prose. *Flexible spiral coverage. *Just-in-time object coverage. *Extensive end-of-chapter problems.

    Understanding the design, implementation, and workings of Mac OS X requires examination of several technologies that differ in their age, origins, philosophies, and roles. Mac OS X Internals: A Systems Approach is the first book that dissects the internals of the system, presenting a detailed picture that grows incrementally as you read. For example, you will learn the roles of the firmware, the bootloader, the Mach and BSD kernel components (including the process, virtual memory, IPC, and file system layers), the object-oriented I/O Kit driver framework, user libraries, and other core pieces of software. You will learn how these pieces connect and work internally, where they originated, and how they evolved. The book also covers several key areas of the Intel-based Macintosh computers.A solid understanding of system internals is immensely useful in design, development, and debugging for programmers of various skill levels. System programmers can use the book as a reference and to construct a better picture of how the core system works. Application programmers can gain a deeper understanding of how their applications interact with the system. System administrators and power users can use the book to harness the power of the rich environment offered by Mac OS X. Finally, members of the Windows, Linux, BSD, and other Unix communities will find the book valuable in comparing and contrasting Mac OS X with their respective systems. Mac OS X Internals focuses on the technical aspects of OS X and is so full of extremely useful information and programming examples that it will definitely become a mandatory tool for every Mac OS X programmer.

    A dirty little secret assembly language programmers rarely admit to, however, is that what you really need to learn is machine organization, not assembly language programming. Write Great Code Vol I, the first in a series from assembly language expert Randall Hyde, dives right into machine organization without the extra overhead of learning assembly language programming at the same time. And since Write Great Code Vol I concentrates on the machine organization, not assembly language, the reader will learn in greater depth those subjects that are language-independent and of concern to a high level language programmer. Write Great Code Vol I will help programmers make wiser choices with respect to programming statements and data types when writing software, no matter which language they use.

     This new edition has an earlier evolution of object concepts, developed in a way that capitalizes on the power of objects without overwhelming beginning programmers. It includes all new Java 5 topics, including Scanner class, enumerated types, autoboxing, variable length parameter lists, the enhanced for loop, and generic types. This is in depth coverage on GUI applications. This book is appropriate for beginning programmers who want to learn to program with Java as well as experienced programmers who want to add Java to their skill-set.

    These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

    There are many sources too for basic information on the extensions to the WWW that permit content to be expressed in natural language yet used by software agents to easily find, share and integrate information. Until now individuals engaged in creating ontologies-- formal descriptions of the concepts, terms, and relationships within a given knowledge domain-- have had no sources beyond the technical standards documents.Semantic Web for the Working Ontologist transforms this information into the practical knowledge that programmers and subject domain experts need. Authors Allemang and Hendler begin with solutions to the basic problems, but don't stop there: they demonstrate how to develop your own solutions to problems of increasing complexity and ensure that your skills will keep pace with the continued evolution of the Semantic Web.

    Many Python developers are now taking an interest in high-level software architecture patterns such as hexagonal/clean architecture, event-driven architecture, and strategic patterns prescribed by domain-driven design (DDD). But translating those patterns into Python isn't always straightforward.With this practical guide, Harry Percival and Bob Gregory from MADE.com introduce proven architectural design patterns to help Python developers manage application complexity. Each pattern is illustrated with concrete examples in idiomatic Python that explain how to avoid some of the unnecessary verbosity of Java and C# syntax. You'll learn how to implement each of these patterns in a Pythonic way.Architectural design patterns include:Dependency inversion, and its links to ports and adapters (hexagonal/clean architecture)Domain-driven design's distinction between entities, value objects, and aggregatesRepository and Unit of Work patterns for persistent storageEvents, commands, and the message busCommand Query Responsibility Segregation (CQRS)Event-driven architecture and reactive microservices