If you look around you will find that all computer systems, from your portable devices to the strongest supercomputers, are heterogeneous in nature. The most obvious heterogeneity is the existence of computing nodes of different capabilities (e.g. multicore, GPUs, FPGAs, ...). But there are also other heterogeneity factors that exist in computing systems, like the memory system components, interconnection, etc. The main reason for these different types of heterogeneity is to have good performance with power efficiency. Heterogeneous computing results in both challenges and opportunities. This book discusses both. It shows that we need to deal with these challenges at all levels of the computing stack: from algorithms all the way to process technology. We discuss the topic of heterogeneous computing from different angles: hardware challenges, current hardware state-of-the-art, software issues, how to make the best use of the current heterogeneous systems, and what lies ahead. The aim of this book is to introduce the big picture of heterogeneous computing. Whether you are a hardware designer or a software developer, you need to know how the pieces of the puzzle fit together. The main goal is to bring researchers and engineers to the forefront of the research frontier in the new era that started a few years ago and is expected to continue for decades. We believe that academics, researchers, practitioners, and students will benefit from this book and will be prepared to tackle the big wave of heterogeneous computing that is here to stay.

To provide the necessary security and quality assurance activities into Internet of Things (IoT)-based software development, innovative engineering practices are vital. They must be given an even higher level of importance than most other events in the field. Integrating the Internet of Things Into Software Engineering Practices provides research on the integration of IoT into the software development life cycle (SDLC) in terms of requirements management, analysis, design, coding, and testing, and provides security and quality assurance activities to IoT-based software development. The content within this publication covers agile software, language specification, and collaborative software and is designed for analysts, security experts, IoT software programmers, computer and software engineers, students, professionals, and researchers.

Chatbots offer exceptional services to end-users due to various factors including the ability to respond to customers' requests quickly according to their convenience. Given the magnitude of research and interest in chatbots, further study on several vital and evolving concerns including human-bot interaction, chatbot adoption, chatbot architecture and design considerations, and chatbot evaluation is required to ensure the technology is utilized appropriately. Trends, Applications, and Challenges of Chatbot Technology provides novel research content and reviews of current chatbot technology and sheds light on challenges and open questions as well as possible research directions. Covering key topics such as human-computer interaction, customer support, and algorithms, this reference work is ideal for computer scientists, industry professionals, policymakers, researchers, academicians, practitioners, scholars, instructors, and students.

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.

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.

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.

Digital image processing is a field that is constantly improving. Gaining high-level understanding from digital images is a key requirement for computing. One aspect of study that is assisting with this advancement is fractal theory. This new science has gained momentum and popularity as it has become a key topic of research in the area of image analysis. Examining Fractal Image Processing and Analysis is an essential reference source that discusses fractal theory applications and analysis, including box-counting analysis, multi-fractal analysis, 3D fractal analysis, and chaos theory, as well as recent trends in other soft computing techniques. Featuring research on topics such as image compression, pattern matching, and artificial neural networks, this book is ideally designed for system engineers, computer engineers, professionals, academicians, researchers, and students seeking coverage on problem-oriented processing techniques and imaging technologies.

In this book the author presents some techniques for exploring trees and graphs. He illustrates the linear search technique and the backtracking technique, and as instances of tree exploration methods he presents various algorithms for parsing subclasses of context-free languages. He also illustrates some tree and graph exploration and manipulation methods by presenting, among others, algorithms for visiting trees, evaluating Boolean expressions, proving propositional formulas, computing paths in graphs, and performing string matching. This book has been used for advanced undergraduate and graduate courses on automata and formal languages, and assumes some prior exposure to the basic notions in that area. Sample programs are presented in Java and Prolog.

The development of software has expanded substantially in recent years. As these technologies continue to advance, well-known organizations have begun implementing these programs into the ways they conduct business. These large companies play a vital role in the economic environment, so understanding the software that they utilize is pertinent in many aspects. Researching and analyzing the tools that these corporations use will assist in the practice of software engineering and give other organizations an outline of how to successfully implement their own computational methods. Tools and Techniques for Software Development in Large Organizations: Emerging Research and Opportunities is an essential reference source that discusses advanced software methods that prominent companies have adopted to develop high quality products. This book will examine the various devices that organizations such as Google, Cisco, and Facebook have implemented into their production and development processes. Featuring research on topics such as database management, quality assurance, and machine learning, this book is ideally designed for software engineers, data scientists, developers, programmers, professors, researchers, and students seeking coverage on the advancement of software devices in today's major corporations.

Complex systems are pervasive in many areas of science. With the increasing requirement for high levels of system performance, complex systems has become an important area of research due to its role in many industries. Advances in System Dynamics and Control provides emerging research on the applications in the field of control and analysis for complex systems, with a special emphasis on how to solve various control design and observer design problems, nonlinear systems, interconnected systems, and singular systems. Featuring coverage on a broad range of topics, such as adaptive control, artificial neural network, and synchronization, this book is an important resource for engineers, professionals, and researchers interested in applying new computational and mathematical tools for solving the complicated problems of mathematical modeling, simulation, and control.