Although the use of cloud computing platforms and applications has expanded rapidly, most books on the subject focus on high-level concepts. There has long been a need for a book that provides detailed guidance on how to develop secure clouds.
Filling this void, Developing and Securing the Cloud provides a comprehensive overview of cloud computing technology. Supplying step-by-step instruction on how to develop and secure cloud computing platforms and web services, it includes an easy-to-understand, basic-level overview of cloud computing and its supporting technologies.
Presenting a framework for secure cloud computing development, the book describes supporting technologies for the cloud such as web services and security. It details the various layers of the cloud computing framework, including the virtual machine monitor and hypervisor, cloud data storage, cloud data management, and virtual network monitor. It also provides several examples of cloud products and prototypes, including private, public, and U.S. government clouds.
Reviewing recent developments in cloud computing, the book illustrates the essential concepts, issues, and challenges in developing and securing today s cloud computing platforms and applications. It also examines prototypes built on experimental cloud computing systems that the author and her team have developed at the University of Texas at Dallas.
This diverse reference is suitable for those in industry, government, and academia. Technologists will develop the understanding required to select the appropriate tools for particular cloud applications. Developers will discover alternative designs for cloud development, and managers will understand if it s best to build their own clouds or contract them out.

Want to kill it at your job interview in the tech industry? Want to win that coding competition? Learn all the algorithmic techniques and programming skills you need from two experienced coaches, problem setters, and jurors for coding competitions. The authors highlight the versatility of each algorithm by considering a variety of problems and show how to implement algorithms in simple and efficient code. Readers can expect to master 128 algorithms in Python and discover the right way to tackle a problem and quickly implement a solution of low complexity. Classic problems like Dijkstra's shortest path algorithm and Knuth-Morris-Pratt's string matching algorithm are featured alongside lesser known data structures like Fenwick trees and Knuth's dancing links. The book provides a framework to tackle algorithmic problem solving, including: Definition, Complexity, Applications, Algorithm, Key Information, Implementation, Variants, In Practice, and Problems. Python code included in the book and on the companion website.

With the rapid growth of technology in society, communication networks have become a heavily researched topic. Implementing these advanced systems is a challenge, however, due to the abundance of optimization problems within these networks. The use of meta-heuristic algorithms and nature-inspired computing has become a prevalent technique among researchers for solving these complex problems within communication networks. Despite its popularity, this specific computing technique lacks the appropriate amount of research that is needed for professionals to grasp a definite understanding. Nature-Inspired Computing Applications in Advanced Communication Networks is a collection of innovative research on the methods and applications of natural computation techniques and algorithms within communication systems such as wireless sensor networks, vehicular adhoc networks, and internet of things. While highlighting topics including mobile sensor deployment, routing optimization, and sleep scheduling, this book is ideally designed for researchers, network professionals, computer scientists, mathematicians, developers, scholars, educators, and students seeking to enhance their understanding of nature-inspired computing and its solutions within various advanced communication networks.

Computer systems have become an important element of the world economy, with billions of dollars spent each year on development, manufacture, operation, and maintenance. Combining coverage of computer system reliability, safety, usability, and other related topics into a single volume, Computer System Reliability: Safety and Usability eliminates the need to consult many different and diverse sources in the hunt for the information required to design better computer systems. After presenting introductory aspects of computer system reliability such as safety, usability-related facts and figures, terms and definitions, and sources for obtaining useful information on computer system reliability, safety, and usability, the book: Reviews mathematical concepts considered useful to understanding subsequent chapters Presents various introductory aspects of reliability, safety, and usability and computer system reliability basics Covers software reliability assessment and improvement methods Discusses important aspects of software quality and human error and software bugs in computer systems Highlights software safety and Internet reliability Details important aspects of software usability including the need for considering usability during the software development phase, software usability engineering process, software usability inspection methods, software usability test methods, and guidelines for conducting software usability testing Elucidates web usability facts and figures, common design errors, web page design, tools for evaluating web usability, and questions to evaluate website message communication effectiveness Examines important aspects of computer system life cycle costing Written by systems reliability expert B.S. Dhillon, the book is accessible to all levels of readership, making it useful to beginners and seasoned professiona

The C programming language is a popular language in industries as well as academics. Since its invention and standardized as ANSI C, several other standards known as C99, C11, and C17 were published with new features in subsequent years. This book covers all the traits of ANSI C and includes new features present in other standards. The content of this book helps a beginner to learn the fundamental concept of the C language. The book contains a step-by-step explanation of every program that allows a learner to understand the syntax and builds a foundation to write similar programs. The explanation clarity, exercises, and illustrations present in this book make it a complete textbook in all aspects. Features: Other than ANSI C, the book explains the new C standards like C99, C11, and C17. Most basic and easy-to-follow programs are chosen to explain the concepts and their syntax. More emphasis is given to the topics like Functions, Pointers, and Structures. Recursion is emphasized with numerous programming examples and diagrams. A separate chapter on the command-line argument and preprocessors is included that concisely explains their usage. Several real-life figures are taken to explain the concepts of dynamic memory allocation, file handling, and the difference between structure and union. The book contains more than 260 illustrations, more than 200 programs, and exercises at the end of each chapter. This book serves as a textbook for UG/PG courses in science and engineering. The researcher, postgraduate engineers, and embedded software developers can also keep this book as reference material for their fundamental learning.

Survival analysis uses statistics to calculate time to failure. Survival Analysis with Python takes a fresh look at this complex subject by explaining how to use the Python programming language to perform this type of analysis. As the subject itself is very mathematical and full of expressions and formulations, the book provides detailed explanations and examines practical implications. The book begins with an overview of the concepts underpinning statistical survival analysis. It then delves into Parametric models with coverage of Concept of maximum likelihood estimate (MLE) of a probability distribution parameter MLE of the survival function Common probability distributions and their analysis Analysis of exponential distribution as a survival function Analysis of Weibull distribution as a survival function Derivation of Gumbel distribution as a survival function from Weibull Non-parametric models including Kaplan-Meier (KM) estimator, a derivation of expression using MLE Fitting KM estimator with an example dataset, Python code and plotting curves Greenwood's formula and its derivation Models with covariates explaining The concept of time shift and the accelerated failure time (AFT) model Weibull-AFT model and derivation of parameters by MLE Proportional Hazard (PH) model Cox-PH model and Breslow's method Significance of covariates Selection of covariates The Python lifelines library is used for coding examples. By mapping theory to practical examples featuring datasets, this book is a hands-on tutorial as well as a handy reference.

Figure 1.1. An outdoor scene "A bus is passing three cars which are parking between trees at the side of the road. Houses having two storeys are lined up at the street. 3 4 Introduction Figure 1.2. An assembly scene There seems to be a small open place between the group of houses in the foreground and the store in the background." In such or a similar way the content of the natural scene shown above can be described. It is quite easy to give such a short description. The problem is somewhat more complex for the second image. First of all, it can be stated that the image does not show an everyday scene. It appears as a kind of man made surrounding. But everyone can accept the following statements about this image: 1. The image shows a snapshot of an assembly line. 2. The robot in front is screwing. 3. There is no person in the working area of the robots. 4. All objects on the conveyor belt are worked on by robots. There are no free objects on the belt.

The bestselling beginner Arduino guide, updated with new projects! Exploring Arduino makes electrical engineering and embedded software accessible. Learn step by step everything you need to know about electrical engineering, programming, and human-computer interaction through a series of increasingly complex projects. Arduino guru Jeremy Blum walks you through each build, providing code snippets and schematics that will remain useful for future projects. Projects are accompanied by downloadable source code, tips and tricks, and video tutorials to help you master Arduino. You'll gain the skills you need to develop your own microcontroller projects! This new 2nd edition has been updated to cover the rapidly-expanding Arduino ecosystem, and includes new full-color graphics for easier reference. Servo motors and stepper motors are covered in richer detail, and you'll find more excerpts about technical details behind the topics covered in the book. Wireless connectivity and the Internet-of-Things are now more prominently featured in the advanced projects to reflect Arduino's growing capabilities. You'll learn how Arduino compares to its competition, and how to determine which board is right for your project. If you're ready to start creating, this book is your ultimate guide! * Get up to date on the evolving Arduino hardware, software, and capabilities * Build projects that interface with other devices wirelessly! * Learn the basics of electrical engineering and programming * Access downloadable materials and source code for every project Whether you're a first-timer just starting out in electronics, or a pro looking to mock-up more complex builds, Arduino is a fantastic tool for building a variety of devices. This book offers a comprehensive tour of the hardware itself, plus in-depth introduction to the various peripherals, tools, and techniques used to turn your little Arduino device into something useful, artistic, and educational. Exploring Arduino is your roadmap to adventure start your journey today!

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.

IT projects emerge from a business need. In practice, software developers must accomplish two big things before an IT project can begin: find out what you need to do (i.e., analyse business requirements) and plan out how to do it (i.e., project management). The biggest problem in IT projects is delivering the wrong product because IT people do not understand what business people require. This practical textbook teaches computer science students how to manage and deliver IT projects by linking business and IT requirements with project management in an incremental and straightforward approach. Business Analysis, Requirements, and Project Management: A Guide for Computing Students presents an approach to analysis management that scales the business perspective. It takes a business process view of a business proposal as a model and explains how to structure a technical problem into a recognisable pattern with problem frames. It shows how to identify core transactions and model them as use cases to create a requirements table useful to designers and coders. Linked to the analysis are three management tools: the product breakdown structure (PBS), the Gantt chart, and the Kanban board. The PBS is derived in part from the problem frame. The Gantt chart emerges from the PBS and ensures the key requirements are addressed by reference to use cases. The Kanban board is especially useful in Task Driven Development, which the text covers. This textbook consists of two interleaving parts and features a single case study. Part one addresses the business and requirements perspective. The second integrates core project management approaches and explains how both requirements and management are connected. The remainder of the book is appendices, the first of which provides solutions to the exercises presented in each chapter. The second appendix puts together much of the documentation for the case study into one place. The case study presents a real-word business scenario to expose students to professional practice.

Need to learn how to wrap your head around Git, but don't need a lot of hand holding? Grab this book if you're new to Git, not to the world of programming. Git tasks displayed on two-page spreads provide all the context you need, without the extra fluff.Get up to speed on Git right now with "Pragmatic Guide to Git." Task-oriented two-page spreads get you up and running with minimal fuss. Each left-hand page dives into the underlying implementation for each task. The right-hand page contains commands that focus on the task at hand, and cross references to other tasks that are related. You'll find what you need fast.Git is rapidly becoming the de-facto standard for the open source community. Its excellent merging capabilities, coupled with its speed and relative ease of use, make it an indispensable tool for any developer. New Git users will learn the basic tasks needed to work with Git every day, including working with remote repositories, dealing with branches and tags, exploring the history, and fixing problems when things go wrong. If you're already familiar with Git, this book will be your go-to reference for Git commands and best practices.You won't find a more practical approach to learning Git than "Pragmatic Guide to Git."

What will you learn from this book? Many people who use Git rely on "recipes"--copying and pasting commands they find on the internet without really understanding how Git actually works. But what do you do if you find yourself in a tight spot? You can't simply wing it. With this unique hands-on guide, you'll learn the ways of Git and have fun while doing it. Raju Gandhi peels back the layers to reveal the simple yet powerful engine that powers Git, so you'll understand not just the how but the why. You'll master branches, merges, commit messages, search, utilities, and more; learn best practices for collaborative work; and unlock the full potential of Git. What's so special about this book? If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. If you haven't, you're in for a treat. With this book, you'll learn Git through a multisensory experience that engages your mind rather than a text-heavy approach that puts you to sleep.

Maintaining a practical perspective, Python Programming: A Practical Approach acquaints you with the wonderful world of programming. The book is a starting point for those who want to learn Python programming. The backbone of any programming, which is the data structure and components such as strings, lists, etc., have been illustrated with many examples and enough practice problems to instill a level of self-confidence in the reader. Drawing on knowledge gained directly from teaching Computer Science as a subject and working on a wide range of projects related to ML, AI, deep learning, and blockchain, the authors have tried their best to present the necessary skills for a Python programmer. Once the foundation of Python programming is built and the readers are aware of the exact structure, dimensions, processing, building blocks, and representation of data, they can readily take up their specific problems from the area of interest and solve them with the help of Python. These include, but are not limited to, operators, control flow, strings, functions, module processing, object-oriented programming, exception and file handling, multithreading, synchronization, regular expressions, and Python database programming. This book on Python programming is specially designed to keep readers busy with learning fundamentals and generates a sense of confidence by attempting the assignment problems. We firmly believe that explaining any particular technology deviates from learning the fundamentals of a programming language. This book is focused on helping readers attempt implementation in their areas of interest through the skills imparted through this book. We have attempted to present the real essence of Python programming, which you can confidently apply in real life by using Python as a tool. Salient Features Based on real-world requirements and solution. Simple presentation without avoiding necessary details of the topic. Executable programs on almost every topic. Plenty of exercise questions, designed to test readers' skills and understanding. Purposefully designed to be instantly applicable, Python Programming: A Practical Approach provides implementation examples so that the described subject matter can be immediately implemented due to the well-known versatility of Python in handling different data types with ease.

This book covers C-Programming focussing on its practical side. Volume 2 deals mainly with composite data structures and their composition. An extensive use of figures and examples help to give a clear description of concepts and help the reader to gain a systematic understanding of the programming language.

Covers IoT-cloud convergence with a focus on complex industrial IoT case studies Discusses the broad background of IoT-cloud convergence architectures and their fundamentals along with resource provisioning mechanisms Emphasizes the use of context in developing context aware IoT solutions Presents a novel C-model that explains the IoT application development phases Discusses a simplified convergence model that depicts the role of cloud in an IoT application

This volume contains selected tutorial and young scientist school papers of the 5th RAAI Summer School on Artificial Intelligence, held in July 2019 at Institute of Physics and Technology (MIPT) campus in Dolgoprudny, a suburb of Moscow, Russia. The 11 chapters in this volume present papers focusing on various important aspects of Multiagent systems; Behavior planning; Natural language processing; Modeling of reasoning; and Machine learning and data analysis.

Learn the essentials of working with Flutter and Dart to build full stack applications that meet the needs of a cloud-driven world. Together, the Flutter open source UI software development kit and the Dart programming language for client development provide a unified solution to building applications capable of targeting multiple platforms. Recipes in this cookbook show you how this potent combination provides an efficient approach to application development. Typically used in frontend development, Flutter helps you develop cross-platform applications for Android, iOS, Linux, Mac, Windows, and the Google Fuchsia operating system. The Dart SDK provides native access to third-party solutions, including APIs, databases, and authentication. When used in concert with Flutter, Dart allows you to compile source code ahead of time to native code. This cookbook shows you how to: Write effective Dart code by using variables and data structures Build applications with Flutter by exploring widgets and data handling Understand cloud provider solutions and learn how to integrate them with Flutter Manage data through APIs using Google Cloud Serverless Work with Firebase solutions such as Authentication and the Cloud Firestore database Build web applications that also work with mobile and desktop platforms

This book covers C-Programming focussing on its practical side. Volume 1 deals mainly with basic data structures, algorithms and program statements. An extensive use of figures and examples help to give a clear description of concepts help the reader to gain a systematic understanding of the language.

Software Engineering: A Methodical Approach (Second Edition) provides a comprehensive, but concise introduction to software engineering. It adopts a methodical approach to solving software engineering problems, proven over several years of teaching, with outstanding results. The book covers concepts, principles, design, construction, implementation, and management issues of software engineering. Each chapter is organized systematically into brief, reader-friendly sections, with itemization of the important points to be remembered. Diagrams and illustrations also sum up the salient points to enhance learning. Additionally, the book includes the author's original methodologies that add clarity and creativity to the software engineering experience. New in the Second Edition are chapters on software engineering projects, management support systems, software engineering frameworks and patterns as a significant building block for the design and construction of contemporary software systems, and emerging software engineering frontiers. The text starts with an introduction of software engineering and the role of the software engineer. The following chapters examine in-depth software analysis, design, development, implementation, and management. Covering object-oriented methodologies and the principles of object-oriented information engineering, the book reinforces an object-oriented approach to the early phases of the software development life cycle. It covers various diagramming techniques and emphasizes object classification and object behavior. The text features comprehensive treatments of: Project management aids that are commonly used in software engineering An overview of the software design phase, including a discussion of the software design process, design strategies, architectural design, interface design, database design, and design and development standards User interface design Operations design Design considerations including system catalog, product documentation, user message management, design for real-time software, design for reuse, system security, and the agile effect Human resource management from a software engineering perspective Software economics Software implementation issues that range from operating environments to the marketing of software Software maintenance, legacy systems, and re-engineering This textbook can be used as a one-semester or two-semester course in software engineering, augmented with an appropriate CASE or RAD tool. It emphasizes a practical, methodical approach to software engineering, avoiding an overkill of theoretical calculations where possible. The primary objective is to help students gain a solid grasp of the activities in the software development life cycle to be confident about taking on new software engineering projects.

Software testing is needed to assess the quality of developed software. However, it consumes a critical amount of time and resources, often delaying the software release date and increasing the overall cost. The answer to this problem is effective test automation, which is expected to meet the need for effective software testing while reducing amount of required time and resources. Advanced Automated Software Testing: Frameworks for Refined Practice discusses the current state of test automation practices, as it includes chapters related to software test automation and its validity and applicability in different domains. This book demonstrates how test automation can be used in different domains and in the different tasks and stages of software testing, making it a useful reference for researchers, students, and software engineers.

This book constitutes the refereed post-conference proceedings of the 5th International Conference on Cryptology and Information Security in Latin America, LATINCRYPT 2017, held in Havana, Cuba, in September 2017. The 20 papers presented were carefully reviewed and selected from 64 submissions. They are organized in the following topical sections: security protocols; public-key implementation; cryptanalysis; theory of symmetric-key cryptography; multiparty computation and privacy; new constructions; and adversarial cryptography.

This book constitutes the proceedings of the 23rd International Conference on Developments in Language Theory, DLT 2019, held in Warsaw, Poland, in August 2019. The 20 full papers presented together with three invited talks were carefully reviewed and selected from 30 submissions. The papers cover the following topics and areas: combinatorial and algebraic properties of words and languages; grammars, acceptors and transducers for strings, trees, graphics, arrays; algebraic theories for automata and languages; codes; efficient text algorithms; symbolic dynamics; decision problems; relationships to complexity theory and logic; picture description and analysis, polyominoes and bidimensional patterns; cryptography; concurrency; celluar automata; bio-inspired computing; quantum computing.

This book constitutes the refereed proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE 2018, held in Funchal, Madeira, Portugal, in March 2018. The 17 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 95 submissions. The papers are organized in topical sections on service science and business information systems and software engineering.

This book constitutes the refereed proceedings of the 9th International Symposium on Business Modeling and Software Design, BMSD 2019, held in Lisbon, Portugal, in July 2019. It contains 12 full and 11 short papers. BMSD is a leading international forum that brings together researchers and practitioners interested in business modeling and its relation to software design. Particular areas of interest are: Business Processes and Enterprise Engineering; Business Models and Requirements; Business Models and Services; Business Models and Software; Information Systems Architectures and Paradigms; Data Aspects in Business Modeling and Software Development; Blockchain-Based Business Models and Information Systems; IoT and Implications for Enterprise Information Systems. The theme of BMSD 2019 was: REFLECTING HUMAN AUTHORITY AND RESPONSIBILITY IN ENTERPRISE MODELS AND SOFTWARE SPECIFICATIONS.

The four-volume set LNCS 11583, 11584, 11585, and 11586 constitutes the proceedings of the 8th International Conference on Design, User Experience, and Usability, DUXU 2019, held as part of the 21st International Conference, HCI International 2019, which took place in Orlando, FL, USA, in July 2019. The total of 1274 papers and 209 posters included in the 35 HCII 2019 proceedings volumes was carefully reviewed and selected from 5029 submissions. DUXU 2019 includes a total of 167 regular papers, organized in the following topical sections: design philosophy; design theories, methods, and tools; user requirements, preferences emotions and personality; visual DUXU; DUXU for novel interaction techniques and devices; DUXU and robots; DUXU for AI and AI for DUXU; dialogue, narrative, storytelling; DUXU for automated driving, transport, sustainability and smart cities; DUXU for cultural heritage; DUXU for well-being; DUXU for learning; user experience evaluation methods and tools; DUXU practice; DUXU case studies.