The highly dynamic world of information technology service management stresses the benefits of the quick and correct implementation of IT services. A disciplined approach relies on a separate set of assumptions and principles as an agile approach, both of which have complicated implementation processes as well as copious benefits. Combining these two approaches to enhance the effectiveness of each, while difficult, can yield exceptional dividends. Balancing Agile and Disciplined Engineering and Management Approaches for IT Services and Software Products is an essential publication that focuses on clarifying theoretical foundations of balanced design methods with conceptual frameworks and empirical cases. Highlighting a broad range of topics including business trends, IT service, and software development, this book is ideally designed for software engineers, software developers, programmers, information technology professionals, researchers, academicians, and students.

The Wolfram language is the programming language of Mathematica, used increasingly by scientists due to its ease of learning and user-friendliness. This book focuses on applications of the Wolfram language to applied mathematics, physics and chemistry. Topics discussed are broad and comprehensive, from differential equations and special functions to fractals and chess, from electromagnetism and optics to relativity and black holes. There is also extensive coverage of quantum theory and quantum chemistry, and the book is peppered with more than 200 color graphics to aid visualization of these concepts. The program codes are provided online as Mathematica notebooks, allowing readers to modify them and manipulate the graphics in real time. This book should be a valuable resource for researchers, educators and students in science and computing who can profit from a more interactive form of instruction.

Parallelism is the key to achieving high performance in computing. However, writing efficient and scalable parallel programs is notoriously difficult, and often requires significant expertise. To address this challenge, it is crucial to provide programmers with high-level tools to enable them to develop solutions easily, and at the same time emphasize the theoretical and practical aspects of algorithm design to allow the solutions developed to run efficiently under many different settings. This thesis addresses this challenge using a three-pronged approach consisting of the design of shared-memory programming techniques, frameworks, and algorithms for important problems in computing. The thesis provides evidence that with appropriate programming techniques, frameworks, and algorithms, shared-memory programs can be simple, fast, and scalable, both in theory and in practice. The results developed in this thesis serve to ease the transition into the multicore era. The first part of this thesis introduces tools and techniques for deterministic parallel programming, including means for encapsulating nondeterminism via powerful commutative building blocks, as well as a novel framework for executing sequential iterative loops in parallel, which lead to deterministic parallel algorithms that are efficient both in theory and in practice. The second part of this thesis introduces Ligra, the first high-level shared memory framework for parallel graph traversal algorithms. The framework allows programmers to express graph traversal algorithms using very short and concise code, delivers performance competitive with that of highly-optimized code, and is up to orders of magnitude faster than existing systems designed for distributed memory. This part of the thesis also introduces Ligra , which extends Ligra with graph compression techniques to reduce space usage and improve parallel performance at the same time, and is also the first graph processing system to support in-memory graph compression. The third and fourth parts of this thesis bridge the gap between theory and practice in parallel algorithm design by introducing the first algorithms for a variety of important problems on graphs and strings that are efficient both in theory and in practice. For example, the thesis develops the first linear-work and polylogarithmic-depth algorithms for suffix tree construction and graph connectivity that are also practical, as well as a work-efficient, polylogarithmic-depth, and cache-efficient shared-memory algorithm for triangle computations that achieves a 2-5x speedup over the best existing algorithms on 40 cores. This is a revised version of the thesis that won the 2015 ACM Doctoral Dissertation Award.

An integral element of software engineering is model engineering. They both endeavor to minimize cost, time, and risks with quality software. As such, model engineering is a highly useful field that demands in-depth research on the most current approaches and techniques. Only by understanding the most up-to-date research can these methods reach their fullest potential. Advancements in Model-Driven Architecture in Software Engineering is an essential publication that prepares readers to exercise modeling and model transformation and covers state-of-the-art research and developments on various approaches for methodologies and platforms of model-driven architecture, applications and software development of model-driven architecture, modeling languages, and modeling tools. Highlighting a broad range of topics including cloud computing, service-oriented architectures, and modeling languages, this book is ideally designed for engineers, programmers, software designers, entrepreneurs, researchers, academicians, and students.

As human activities moved to the digital domain, so did all the well-known malicious behaviors including fraud, theft, and other trickery. There is no silver bullet, and each security threat calls for a specific answer. One specific threat is that applications accept malformed inputs, and in many cases it is possible to craft inputs that let an intruder take full control over the target computer system. The nature of systems programming languages lies at the heart of the problem. Rather than rewriting decades of well-tested functionality, this book examines ways to live with the (programming) sins of the past while shoring up security in the most efficient manner possible. We explore a range of different options, each making significant progress towards securing legacy programs from malicious inputs. The solutions explored include enforcement-type defenses, which excludes certain program executions because they never arise during normal operation. Another strand explores the idea of presenting adversaries with a moving target that unpredictably changes its attack surface thanks to randomization. We also cover tandem execution ideas where the compromise of one executing clone causes it to diverge from another thus revealing adversarial activities. The main purpose of this book is to provide readers with some of the most influential works on run-time exploits and defenses. We hope that the material in this book will inspire readers and generate new ideas and paradigms.

This book is for novices If you have never done any programming before - if you are a complete novice - this book is for you. This book assumes no prior knowledge of programming. It starts from scratch. It is written in a simple, direct style for maximum clarity. It is aimed at first level students at universities and colleges, but it is also suitable for novices studying alone. The approach of this book We explain how to use objects early in this book. Our approach is to start with the ideas of variables, assignment and methods, then introduce the use of objects created from library classes. Next we explain how to use control structures for selection and looping. Then comes the treatment of how to write your own classes. We wanted to make sure that the fun element of programming was paramount, so we use graphics right from the start. We think graphics is fun, interesting and clearly demonstrates all the important principles of programming. But we haven't ignored programs that input and output text - they are also included. The programs we present use many of the features of a graphical user interfaces (GUIs), such as buttons, scroll bars and text boxes. But we also explain how to write console programs in Java. We introduce new ideas carefully one-at-a-time, rather than all at once. So, for example, there is a single chapter on writing methods. We introduce simple ideas early and more sophisticated ideas later on.

Software development and design is an intricate and complex process that requires a multitude of steps to ultimately create a quality product. One crucial aspect of this process is minimizing potential errors through software fault prediction. Enhancing Software Fault Prediction With Machine Learning: Emerging Research and Opportunities is an innovative source of material on the latest advances and strategies for software quality prediction. Including a range of pivotal topics such as case-based reasoning, rate of improvement, and expert systems, this book is an ideal reference source for engineers, researchers, academics, students, professionals, and practitioners interested in novel developments in software design and analysis.