Advances in Computers, Volume 106 is the latest volume in the series, which has been published since 1960. This update presents innovations in computer hardware, software, theory, design and applications, with new chapters in this volume including sections on A New Course on R&D Project Management in Computer Science and Engineering: Subjects Taught, Rationales Behind, and Lessons Learned, Advances in Dataflow Systems, Adaptation and Evaluation of the Simplex Algorithm for a Data-Flow Architecture, and Simple Operations in Memory to Reduce Data Movement. In addition, this series provides contributors with a medium to explore their subjects in greater depth than journal articles usually allow.

SQL is a widely used to access most databases, therefore database developers and system administrators should be familiar with it. This hands-on SQL book will help beginner and intermediate users to write queries that apply complex conditions on a table. The book's unique side by side approach makes it easy for the reader to learn three major query languages in the IT industry. The author has over 20 years of experience in database design. KEY FEATURES: Contains numerous practical screenshots of Oracle SQL, T-SQL, MySQL statements and results. Shows the differences between Oracle SQL, T-SQL and MySQL side by side. Gives a real world experience for SQL developers and database administrators. Sample data is available to work on (available on our website).

With multicore processors now in every computer, server, and embedded device, the need for cost-effective, reliable parallel software has never been greater. By explaining key aspects of multicore programming, Fundamentals of Multicore Software Development helps software engineers understand parallel programming and master the multicore challenge. Accessible to newcomers to the field, the book captures the state of the art of multicore programming in computer science. It covers the fundamentals of multicore hardware, parallel design patterns, and parallel programming in C++, .NET, and Java. It also discusses manycore computing on graphics cards and heterogeneous multicore platforms, automatic parallelization, automatic performance tuning, transactional memory, and emerging applications. As computing power increasingly comes from parallelism, software developers must embrace parallel programming. Written by leaders in the field, this book provides an overview of the existing and up-and-coming programming choices for multicores. It addresses issues in systems architecture, operating systems, languages, and compilers.

LabVIEW (TM) has become one of the preeminent platforms for the development of data acquisition and data analysis programs. LabVIEW (TM): A Developer's Guide to Real World Integration explains how to integrate LabVIEW into real-life applications. Written by experienced LabVIEW developers and engineers, the book describes how LabVIEW has been pivotal in solving real-world challenges. Each chapter is self-contained and demonstrates the power and simplicity of LabVIEW in various applications, from image processing to solar tracking systems. Many of the chapters explore how exciting new technologies can be implemented in LabVIEW to enable novel solutions to new or existing problems. The text also presents novel tricks and tips for integrating LabVIEW with third-party hardware and software. Ideal for LabVIEW users who develop stand-alone applications, this down-to-earth guide shows how LabVIEW provides solutions to a variety of application problems. It includes projects and virtual instrumentation for most of the programs and utilities described. Many of the authors' own software contributions are available on the downloadable resources.

Emphasizing the connection between mathematical objects and their practical C++ implementation, this book provides a comprehensive introduction to both the theory behind the objects and the C and C++ programming. Object-oriented implementation of three-dimensional meshes facilitates understanding of their mathematical nature. Requiring no prerequisites, the text covers discrete mathematics, data structures, and computational physics, including high-order discretization of nonlinear equations. Exercises and solutions make the book suitable for classroom use and a supporting website supplies downloadable code.

An emerging topic in software engineering and data mining, specification mining tackles software maintenance and reliability issues that cost economies billions of dollars each year. The first unified reference on the subject, Mining Software Specifications: Methodologies and Applications describes recent approaches for mining specifications of software systems. Experts in the field illustrate how to apply state-of-the-art data mining and machine learning techniques to address software engineering concerns. In the first set of chapters, the book introduces a number of studies on mining finite state machines that employ techniques, such as grammar inference, partial order mining, source code model checking, abstract interpretation, and more. The remaining chapters present research on mining temporal rules/patterns, covering techniques that include path-aware static program analyses, lightweight rule/pattern mining, statistical analysis, and other interesting approaches. Throughout the book, the authors discuss how to employ dynamic analysis, static analysis, and combinations of both to mine software specifications. According to the US National Institute of Standards and Technology in 2002, software bugs have cost the US economy 59.5 billion dollars a year. This volume shows how specification mining can help find bugs and improve program understanding, thereby reducing unnecessary financial losses. The book encourages the industry adoption of specification mining techniques and the assimilation of these techniques in standard integrated development environments (IDEs).

Classical FORTRAN: Programming for Engineering and Scientific Applications, Second Edition teaches how to write programs in the Classical dialect of FORTRAN, the original and still most widely recognized language for numerical computing. This edition retains the conversational style of the original, along with its simple, carefully chosen subset language and its focus on floating-point calculations. New to the Second Edition Additional case study on file I/O More about CPU timing on Pentium processors More about the g77 compiler and Linux With numerous updates and revisions throughout, this second edition continues to use case studies and examples to introduce the language elements and design skills needed to write graceful, correct, and efficient programs for real engineering and scientific applications. After reading this book, students will know what statements to use and where as well as why to avoid the others, helping them become expert FORTRAN programmers.

Fast Python for Data Science is a hands-on guide to writing Python code that can process more data, faster, and with less resources. It takes a holistic approach to Python performance, showing you how your code, libraries, and computing architecture interact and can be optimized together. Written for experienced practitioners, Fast Python for Data Science dives right into practical solutions for improving computation and storage efficiency. You'll experiment with fun and interesting examples such as rewriting games in lower-level Cython and implementing a MapReduce framework from scratch. Finally, you'll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working. About the technology Fast, accurate systems are vital for handling the huge datasets and complex analytical algorithms that are common in modern data science. Python programmers need to boost performance by writing faster pure-Python programs, optimizing the use of libraries, and utilizing modern multi-processor hardware; Fast Python for Data Science shows you how.

Have you ever seen a promising project get abandoned right when it seemed like it was getting ready to launch, or a project that always seemed like it was going to launch "next month," but took many months or even years before it actually launched? Scrum may be the solution to such woes. It is a project management methodology that, when applied faithfully, will increase the rate at which your project is completed, the enjoyment your team has while working on it, and its commercial success. Converting to scrum can be a challenge for any team, but it is particularly painful for part time, virtual, and student teams. Successful Scrumbutt helps teams quickly learn scrum project management and adapt it to their unique situations. Author Noah Dyer illustrates key techniques for maintaining a team's productivity and enthusiasm for a project across its lifetime in fun, engaging, and slightly irreverent ways. Key Features Learn key techniques for maintaining enthusiasm for your project across its lifetime and have the confidence that every hour spent on your project is having maximum benefit. Includes instructions for using Assembla and other popular and free Scrum software. This will save people time identifying and learning a software package to help implement Scrum principles. Activities to introduce people to Scrum and practice Scrum principles. These are fun ways to learn Scrum in a low pressure atmosphere where delivery and execution are not paramount. Soft Skills Sections help readers understand not only the action to be taken and the principle, but how to effectively communicate with others regarding Scrum practices, particularly problem solving. Excel templates, activities for implementing Scrum in a low tech environment and planning cards that make Scrum planning activities easier and feel more official are included for download and easy printing. Do It Now: Tips for integrating the principle in a chapter right away, even if full Scrum is not yet fully understood and achievable.

Have you ever seen a promising project get abandoned right when it seemed like it was getting ready to launch, or a project that always seemed like it was going to launch "next month," but took many months or even years before it actually launched? Scrum may be the solution to such woes. It is a project management methodology that, when applied faithfully, will increase the rate at which your project is completed, the enjoyment your team has while working on it, and its commercial success. Converting to scrum can be a challenge for any team, but it is particularly painful for part time, virtual, and student teams. Successful Scrumbutt helps teams quickly learn scrum project management and adapt it to their unique situations. Author Noah Dyer illustrates key techniques for maintaining a team's productivity and enthusiasm for a project across its lifetime in fun, engaging, and slightly irreverent ways. Key Features Learn key techniques for maintaining enthusiasm for your project across its lifetime and have the confidence that every hour spent on your project is having maximum benefit. Includes instructions for using Assembla and other popular and free Scrum software. This will save people time identifying and learning a software package to help implement Scrum principles. Activities to introduce people to Scrum and practice Scrum principles. These are fun ways to learn Scrum in a low pressure atmosphere where delivery and execution are not paramount. Soft Skills Sections help readers understand not only the action to be taken and the principle, but how to effectively communicate with others regarding Scrum practices, particularly problem solving. Excel templates, activities for implementing Scrum in a low tech environment and planning cards that make Scrum planning activities easier and feel more official are included for download and easy printing. Do It Now: Tips for integrating the principle in a chapter right away, even if full Scrum is not yet fully understood and achievable.

Discover the do's and don'ts involved in crafting readable Swift code as you explore common Swift coding challenges and the best practices that address them. From spacing, bracing, and semicolons to proper API style, discover the whys behind each recommendation, and add to or establish your own house style guidelines. This practical, powerful, and opinionated guide offers the best practices you need to know to work successfully in this equally opinionated programming language. Apple's Swift programming language has finally reached stability, and developers are demanding to know how to program the language properly. Swift Style guides you through the ins and outs of Swift programming best practices. This is the first best practices book for serious, professional Swift programmers and for programmers who want to shine their skills to be hired in this demanding market. A style guide offers a consistent experience of well-crafted code that lets you focus on the code's underlying meaning, intent, and implementation. This book doesn't offer canonical answers on Swift coding style. It explores the areas of Swift where structure comes into play. Whether you're developing a personal style or a house style, there are always ways to enhance your code choices. You'll find here the ideas and principles to establish or enhance your own best style practices. Begin with simple syntactical styling. Strengthen code bracing for easy readability. Style your closures for safety and resilience. Perfect spacing and layout. Master literal initialization and typing. Optimize control flow layout and improve conditional style choices. Transition from Objective-C and move code into Swift the right way. Boost API design using proper naming and labeling. Elevate defaulted arguments and variadics to their right places. Finally, Erica offers her own broad recommendations on good coding practice. What You Need: Recent version of the Swift programming language

Property-based testing helps you create better, more solid tests with little code. By using the PropEr framework in both Erlang and Elixir, this book teaches you how to automatically generate test cases, test stateful programs, and change how you design your software for more principled and reliable approaches. You will be able to better explore the problem space, validate the assumptions you make when coming up with program behavior, and expose unexpected weaknesses in your design. PropEr will even show you how to reproduce the bugs it found. With this book, you will be writing efficient property-based tests in no time. Most tests only demonstrate that the code behaves how the developer expected it to behave, and therefore carry the same blind spots as their authors when special conditions or edge cases show up. Learn how to see things differently with property tests written in PropEr. Start with the basics of property tests, such as writing stateless properties, and using the default generators to generate test cases automatically. More importantly, learn how to think in properties. Improve your properties, write custom data generators, and discover what your code can or cannot do. Learn when to use property tests and when to stick with example tests with real-world sample projects. Explore various testing approaches to find the one that's best for your code. Shrink failing test cases to their simpler expression to highlight exactly what breaks in your code, and generate highly relevant data through targeted properties. Uncover the trickiest bugs you can think of with nearly no code at all with two special types of properties based on state transitions and finite state machines. Write Erlang and Elixir properties that generate the most effective tests you'll see, whether they are unit tests or complex integration and system tests. What You Need Basic knowledge of Erlang, optionally Elixir For Erlang tests: Erlang/OTP >= 20.0, with Rebar >= 3.4.0 For Elixir tests: Erlang/OTP >= 20.0, Elixir >= 1.5.0

The book is a collection of invited chapters by renowned experts and is part of a series on Language Processing, Pattern Recognition, and Intelligent Systems. The content is wide-ranging, encompassing perspectives from computer science to social science to design and reflecting the considerable experience of researchers, teachers and practitioners. This diversity offers rigorous approaches to the topic of Digital fonts and reading, organised in four sections: vision and reading; scientific approaches to reading; perspectives on type design practice; and using type. The heavily illustrated text includes original research, case studies, reviews, and practical advice, serving as a useful handbook or reference to inform design for reading. Traditionally, there has been a separation between researchers and practitioners, with different agendas. This book bridges the gap between scientific testing and design experience and considers the reader's perspective. The collection aims to resonate with academics and students, experienced or novice typographic or interface designers and software engineers, and engage with anyone who has an interest in type and reading.

The second edition of C# and Game Programming offers the same practical, hands-on approach as the first edition to learning the C# language through classic arcade game applications. Complete source code for games like Battle Bit, Asteroid Miner, and Battle Tennis, included on the CD-ROM, demonstrates programming strategies and complements the comprehensive treatment of C# in the text. From the basics of adding graphics and sound to games, to advanced concepts such as the .Net framework and object-oriented programming, this book provides the foundations for a beginner to become a full-fledged programmer. New in this edition: - Supports DirectX 9.0 - Revised programs and examples - Improved frame rate for game examples

Combining knowledge with strategies, Data Structure Practice for Collegiate Programming Contests and Education presents the first comprehensive book on data structure in programming contests. This book is designed for training collegiate programming contest teams in the nuances of data structure and for helping college students in computer-related majors to gain deeper understanding of data structure. Based on successful experiences in many world-level contests, the book includes 204 typical problems and detailed analyses selected from the ACM International Collegiate Programming Contest and other major programming contests since 1990. It is divided into four sections that focus on: Fundamental programming skills Experiments for linear lists Experiments for trees Experiments for graphs Each chapter contains a set of problems and includes hints. The book also provides test data for most problems as well as sources and IDs for online judgments that help with improving programming skills. Introducing a multi-options model and considerations of context, Data Structure Practice for Collegiate Programming Contests and Education encourages students to think creatively in solving programming problems. By taking readers through practical contest problems from analysis to implementation, it provides a complete source for enhancing understanding and polishing skills in programming.

* Targests readers with a background in programming, interested in an introduction/refresher in statistical hypothesis testing * Uses Python throughout * Provides the reader with the opportunity of using the book whenever needed rather than following a sequential path.

A novel approach for the classroom or self-study, Learn to Code with Games makes coding accessible to a broad audience. Structured as a series of challenges that help you learn to code by creating a video game, each chapter expands and builds your knowledge while providing guidelines and hints to solving each challenge. The book employs a unique problem-solving approach to teach you the technical foundations of coding, including data types, variables, functions, and arrays. You will also use techniques such as pseudocode and process mapping to formulate solutions without needing to type anything into a computer, and then convert the solutions into executable code. Avoiding jargon as much as possible, Learn to Code with Games shows you how to see coding as a way of thinking and problem solving rather than a domain of obscure languages and syntaxes. Its practical hands-on approach through the context of game development enables you to easily grasp basic programming concepts.

General Purpose Simulation System (GPSS) is a special computer programming language primarily used to simulate what can be classified as discrete systems. A discrete system is one where, at any given instant in time, a countable number of things can take place. The basic operation of a mine itself can be considered such a system. Discrete Simulation and Animation for Mining Engineers explains how to model mining systems using GPSS/H (R) and PROOF (R) by Wolverine Software Corporation. Employing a unique approach that encourages engagement from the start, the text discusses animation first, and then slowly introduces simulation language. As each new topic is covered, an animation is provided to illustrate the key concepts.Leveraging valuable insight gained from the author's extensive experience modeling mines around the world, the book: Describes how to apply discrete system simulation to mines Shows how to make those simulations come alive with animation Includes real-world examples and exercises that hone practical problem-solving skills Written by a mining engineer for mining engineers and students of mining, Discrete Simulation and Animation for Mining Engineers offers a comprehensive yet accessible treatment of mine simulation and animation useful in increasing the efficiency of industrial mining processes.

Features Teaches software design by showing programmers how to build the tools they use every day. Each chapter includes exercises to help readers check and deepen their understanding. All the example code can be downloaded, re-used, and modified under an open license.

Features Connected to a Github repository with the codes in the book. The repository can be accessed at https://bit.ly/3bllnuf Suitable for undergraduate students, as well as anyone who wants a gentle introduction to the principles of quantitative finance No pre-requisites required for programming or advanced mathematics beyond basic calculus.

You know how to code in Elixir; now learn to think in it. Learn to design libraries with intelligent layers that shape the right data structures, flow from one function into the next, and present the right APIs. Embrace the same OTP that's kept our telephone systems reliable and fast for over 30 years. Move beyond understanding the OTP functions to knowing what's happening under the hood, and why that matters. Using that knowledge, instinctively know how to design systems that deliver fast and resilient services to your users, all with an Elixir focus. Elixir is gaining mindshare as the programming language you can use to keep you software running forever, even in the face of unexpected errors and an ever growing need to use more processors. This power comes from an effective programming language, an excellent foundation for concurrency and its inheritance of a battle-tested framework called the OTP. If you're using frameworks like Phoenix or Nerves, you're already experiencing the features that make Elixir an excellent language for today's demands. This book shows you how to go beyond simple programming to designing, and that means building the right layers. Embrace those data structures that work best in functional programs and use them to build functions that perform and compose well, layer by layer, across processes. Test your code at the right place using the right techniques. Layer your code into pieces that are easy to understand and heal themselves when errors strike. Of all Elixir's boons, the most important one is that it guides us to design our programs in a way to most benefit from the architecture that they run on. The experts do it and now you can learn to design programs that do the same. What You Need: Elixir Version 1.7 or greater.

This easy-to-follow textbook provides a student-friendly introduction to programming and algorithms. Emphasis is placed on the threshold concepts that present barriers to learning, including the questions that students are often too embarrassed to ask. The book promotes an active learning style in which a deeper understanding is gained from evaluating, questioning, and discussing the material, and practised in hands-on exercises. Although R is used as the language of choice for all programs, strict assumptions are avoided in the explanations in order for these to remain applicable to other programming languages. Features: provides exercises at the end of each chapter; includes three mini projects in the final chapter; presents a list of titles for further reading at the end of the book; discusses the key aspects of loops, recursions, program and algorithm efficiency and accuracy, sorting, linear systems of equations, and file processing; requires no prior background knowledge in this area.

Interactive data supports organizations to communicate effectively with their stakeholders and partners on the Internet and the World Wide Web. XBRL (eXtensible Business Reporting Language) is a key enabling technology for interactive data. XBRL links organizations and knowledge consumers in a variety of information value chains. XBRL is now in use in many countries and important settings. This book provides, for the first time, an in-depth analysis of XBRL. Thorough and up-to-date, this book explains the most popular constructs in XML, on which XBRL builds, and XBRL. The book provides business and policy makers, technologists and information engineers with an essential toolkit to understand the complete implementation of XBRL. The book begins with an overview of the business case for interactive data and XBRL. There is an introduction to XML and XBRL and the design and construction of XBRL taxonomies including extensions and multi-dimensional XBRL implementations. It provides a detailed analysis of the interaction of instance documents and taxonomies. The book also provides a synopsis of the most current XBRL technologies.

It's time to dispel the myth that machine learning is difficult. Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math. No specialist knowledge is required to tackle the hands-on exercises using readily available machine learning tools! In Grokking Machine Learning, expert machine learning engineer Luis Serrano introduces the most valuable ML techniques and teaches you how to make them work for you. Practical examples illustrate each new concept to ensure you're grokking as you go. You'll build models for spam detection, language analysis, and image recognition as you lock in each carefully-selected skill. Packed with easy-to-follow Python-based exercises and mini-projects, this book sets you on the path to becoming a machine learning expert. Key Features * Different types of machine learning, including supervised and unsupervised learning * Algorithms for simplifying, classifying, and splitting data * Machine learning packages and tools * Hands-on exercises with fully-explained Python code samples For readers with intermediate programming knowledge in Python or a similar language. About the technology Machine learning is a collection of mathematically-based techniques and algorithms that enable computers to identify patterns and generate predictions from data. This revolutionary data analysis approach is behind everything from recommendation systems to self-driving cars, and is transforming industries from finance to art. Luis G. Serrano has worked as the Head of Content for Artificial Intelligence at Udacity and as a Machine Learning Engineer at Google, where he worked on the YouTube recommendations system. He holds a PhD in mathematics from the University of Michigan, a Bachelor and Masters from the University of Waterloo, and worked as a postdoctoral researcher at the University of Quebec at Montreal. He shares his machine learning expertise on a YouTube channel with over 2 million views and 35 thousand subscribers, and is a frequent speaker at artificial intelligence and data science conferences.

Although industry has been leveraging the advancements of component-oriented development and assembly (CODA) technology for some time, there has long been a need for a book that provides a complete overview of the multiple technologies that support CODA. Filling this need, Component-Oriented Development and Assembly supplies comprehensive coverage of the principles, practice, and paradigm of component-oriented development and assembly. The first part of the book provides the conceptual foundation for component-oriented software. Part II focuses on the various standard Java component models and describes how to develop a component-oriented system using these component models. Part III covers the various aspects of the component-oriented development paradigm. Based on the authors' research and teaching experience, the text focuses on the principles of component-oriented software development from a technical concepts perspective, designer's perspective, programmer's perspective, and manager's perspective. Covering popular component development frameworks based on Java, it is suitable as a textbook for component-oriented software for undergraduate and postgraduate courses. It is also an ideal reference for anyone looking to adopt the component-oriented development paradigm. The book provides readers with access to all the source code used in the book on a companion site (http://www.codabook.com). The source code for the CODA implementation of the case study presented in Chapter 11 is also hosted on the website. The website will also serve as a technical forum for further discussions on the topic and for any updates to the book.