The programs contained in the book are not artificial, but are actual programs ae tools which have proved valuable in the production of other programs.Modern programming techniques such as structured programming and top-down design are emphasized and applied to every program. The programs are presented in a structured language called Ratfor ("Rational Fortran") which can be easily understood by anyone familiar with Fortran or PL/I, Algol, PASCAL, or similar languages. (Ratfor translates readily into Fortran or PL/I. One of the tools presented is a preprocessor to translate Ratfor into Fortran). All of the programs are complete and have been tested directly from the text. The programs are available in machine-readable form from Addison-Wesley.Software Tools is ideal for use in a "software engineering" course, for a second course in programming, or as a supplement in any programming course. All programmers, professional and student, will find the book invaluable as a source of proven, useful programs for reading and study. Numerous exercises are provided to test comprehension and to extend the concepts presented in the text.

    The new edition provides invitations - not requirements - to use technology, as well as new conceptual problems, and new projects that focus on writing and working in teams.

    This book surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use.The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts.The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants.Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.

    The authors are well-known for their clear presentation that makes the material accessible to a a broad audience and requires no special previous mathematical experience. KEY TOPICS: In this new edition, the authors incorporate a somewhat more informal, friendly writing style to present both classical and contemporary theories of computation. Algorithms, complexity analysis, and algorithmic ideas are introduced informally in Chapter 1, and are pursued throughout the book. Each section is followed by problems.

    The books also provides a companion web site that provides the toold and materials necessary to build the hardware and software.

     Covers the C++ language, featuring a wealth of tested and debugged working programs in C and C++. Explains and analyzes algorithms -- showing step- by-step solutions to real problems. Presents algorithms as intermediaries between English language descriptions and C programs. Covers classes in C++, including function members, inheritance and object orientation, an example of implementing abstract data types in C++, as well as polymorphism.

    Its humorous title begins with the punch line of a classic joke about someone who is baffled by technology. It was written by a 40-year computer veteran who wants to take the mystery out of computers and allow everyone to gain a true understanding of exactly what computers are, and also what they are not. Years of writing, diagramming, piloting and editing have culminated in one easy to read volume that contains all of the basic principles of computers written so that everyone can understand them. There used to be only two types of book that delved into the insides of computers. The simple ones point out the major parts and describe their functions in broad general terms. Computer Science textbooks eventually tell the whole story, but along the way, they include every detail that an engineer could conceivably ever need to know. Like Momma Bear's porridge, But How Do It Know? is just right, but it is much more than just a happy medium. For the first time, this book thoroughly demonstrates each of the basic principles that have been used in every computer ever built, while at the same time showing the integral role that codes play in everything that computers are able to do. It cuts through all of the electronics and mathematics, and gets right to practical matters. Here is a simple part, see what it does. Connect a few of these together and you get a new part that does another simple thing. After just a few iterations of connecting up simple parts - voilà! - it's a computer. And it is much simpler than anyone ever imagined. But How Do It Know? really explains how computers work. They are far simpler than anyone has ever permitted you to believe. It contains everything you need to know, and nothing you don't need to know. No technical background of any kind is required. The basic principles of computers have not changed one iota since they were invented in the mid 20th century. "Since the day I learned how computers work, it always felt like I knew a giant secret, but couldn't tell anyone," says the author. Now he's taken the time to explain it in such a manner that anyone can have that same moment of enlightenment and thereafter see computers in an entirely new light.

    It contains many puzzles and their solutions and aims to attract many readers in an age where computer science, logic, and mathematics are becoming increasingly important and popular.

    Aiming to tell the dark secrets of computer arithmetic, this title is suitable for library developers, compiler writers, and lovers of elegant hacks.

    “Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior.In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing.www.big-data-book.com

    Learn You a Haskell for Great Good! introduces programmers familiar with imperative languages (such as C++, Java, or Python) to the unique aspects of functional programming. Packed with jokes, pop culture references, and the author's own hilarious artwork, Learn You a Haskell for Great Good! eases the learning curve of this complex language, and is a perfect starting point for any programmer looking to expand his or her horizons. The well-known web tutorial on which this book is based is widely regarded as the best way for beginners to learn Haskell, and receives over 30,000 unique visitors monthly.

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    Topics include the limits of knowledge, paradox of complexity, Maxwell's demon, Big Bang theory, much more. 1985 edition.

    Along the way, there is an abundance of traps that one can fall into, which can derail the best-laid plans and put your projects behind schedule.Cem Kaner, James Bach, and Bret Pettichord know this all too well. Between them, they have over fifty years of testing experience, and know what it takes for successful testing. In this groundbreaking new book, they have compiled 293 pieces of experience-tested advice for you to put to work in your testing projects. They reveal insights on how to do the job well, how to manage it, and how to steer clear of common misunderstandings in software testing. Each lesson is an assertion related to software testing, followed by an explanation or example that shows you the how, when, and why of the testing lesson.The ultimate resource for software testers, developers, and managers at every level of expertise, this guidebook also features:- Useful practices and helpful ways of evaluating situations gleaned from over fifty years of combined testing experience from the world's leading software testing experts- Lessons for all key topic areas including test design, test automation, test management, testing strategies, and bug reporting- Advice on how to match the selection of practices to the circumstances of your project

    Stressing the relationship between system software and the architecture of the machine it is designed to support, Beck first presents the fundamental concepts and basic design of each type of software in a machine-independent way. He then discusses both machine-dependent and independent extensions to the basic concepts, and gives examples of the actual system software. New FeaturesProvides updated architecture and software examples, including the Intel x86 family (Pentium, P6, etc.), IBM PowerPC, Sun SPARC, and Cray T3E. Includes an introduction to object-oriented programming and design, and illustrates these concepts of object-oriented languages, compilers, and operating systems. Brings the book up-to-speed with industry by including current operating systems topics, such as multiprocessor, distributed, and client/server systems. Contains a wide selection of examples and exercises, providing teaching support as well as flexibility, allowing you to concentrate on the software and architectures that you want to cover.