Anyone Can Code: The Art and Science of Logical Creativity introduces computer programming as a way of problem-solving through logical thinking. It uses the notion of modularization as a central lens through which we can make sense of many software concepts. This book takes the reader through fundamental concepts in programming by illustrating them in three different and distinct languages: C/C++, Python, and Javascript. Key features: Focuses on problem-solving and algorithmic thinking instead of programming functions, syntax, and libraries; Includes engaging examples, including video games and visual effects; Provides exercises and reflective questions. This book gives beginner and intermediate learners a strong understanding of what they are doing so that they can do it better and with any other tool or language that they may end up using later.

This brilliant textbook explains in detail the principles of conceptual modeling independently from particular methods and languages and shows how to apply them in real-world projects. The author covers all aspects of the engineering process from structural modeling over behavioral modeling to meta-modeling, and completes the presentation with an extensive case study based on the osCommerce system. Written for computer science students in classes on information systems modeling as well as for professionals feeling the need to formalize their experiences or to update their knowledge, Olive delivers here a comprehensive treatment of all aspects of the modeling process. His book is complemented by lots of exercises and additional online teaching material."

'Evolutionary Computation for Optimization and Modelling' is an introduction to evolutionary computation, selectionist algorithms that operate on populations of structures. It includes over 100 experiments and over 700 homework problems that introduce the topic with an application-oriented approach.

This is the second edition of Wil van der Aalst's seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.

How is it that one system is more effective, appealing, satisfying and/or more beautiful than another to its stakeholder community? This question drove Christopher Alexander's fifty-year quest to explain great physical architecture and gave birth to pattern-languages for building that underpin much of modern systems engineering. How is it that so many individual stakeholders consistently recognize the same quality, the same beauty in a system? This question led George Lakoff to research the role of conceptual metaphor in human understanding. What is essential to stakeholders' satisfaction with systems? Fred Brooks, in his publications, addressed this question. This monograph fuses these diverse streams of thought in proposing Thriving Systems Theory by translating Alexander's properties of physical design quality into the abstract domain of information systems and modeling. Metaphor-Driven Modeling incorporates the theory while examining its impact throughout the system life cycle: modeling, design and deployment. The result is holistic and innovative, a perspective on system quality invaluable to students, practitioners and researchers of software and systems engineering.

Computational Intelligence Techniques and Their Applications to Software Engineering Problems focuses on computational intelligence approaches as applicable in varied areas of software engineering such as software requirement prioritization, cost estimation, reliability assessment, defect prediction, maintainability and quality prediction, size estimation, vulnerability prediction, test case selection and prioritization, and much more. The concepts of expert systems, case-based reasoning, fuzzy logic, genetic algorithms, swarm computing, and rough sets are introduced with their applications in software engineering. The field of knowledge discovery is explored using neural networks and data mining techniques by determining the underlying and hidden patterns in software data sets. Aimed at graduate students and researchers in computer science engineering, software engineering, information technology, this book: Covers various aspects of in-depth solutions of software engineering problems using computational intelligence techniques Discusses the latest evolutionary approaches to preliminary theory of different solve optimization problems under software engineering domain Covers heuristic as well as meta-heuristic algorithms designed to provide better and optimized solutions Illustrates applications including software requirement prioritization, software cost estimation, reliability assessment, software defect prediction, and more Highlights swarm intelligence-based optimization solutions for software testing and reliability problems

This book presents the analysis, design, documentation, and quality of software solutions based on the OMG UML v2.5. Notably it covers 14 different modelling constructs including use case diagrams, activity diagrams, business-level class diagrams, corresponding interaction diagrams and state machine diagrams. It presents the use of UML in creating a Model of the Problem Space (MOPS), Model of the Solution Space (MOSS) and Model of the Architectural Space (MOAS). The book touches important areas of contemporary software engineering ranging from how a software engineer needs to invariably work in an Agile development environment through to the techniques to model a Cloud-based solution.

There is an intrinsic conflict between creating secure systems and usable systems. But usability and security can be made synergistic by providing requirements and design tools with specific usable security principles earlier in the requirements and design phase. In certain situations, it is possible to increase usability and security by revisiting design decisions made in the past; in others, to align security and usability by changing the regulatory environment in which the computers operate. This book addresses creation of a usable security protocol for user authentication as a natural outcome of the requirements and design phase of the authentication method development life cycle.

Why have a book about the relation between requirements and software architecture? Understanding the relation between requirements and architecture is important because the requirements, be they explicit or implicit, represent the function, whereas the architecture determines the form. While changes to a set of requirements may impact on the realization of the architecture, choices made for an architectural solution may impact on requirements, e.g., in terms of revising functional or non-functional requirements that cannot actually be met.

Although research in both requirements engineering and software architecture is quite active, it is in their combination that understanding is most needed and actively sought. Presenting the current state of the art is the purpose of this book. The editors have divided the contributions into four parts: Part 1 "Theoretical Underpinnings and Reviews" addresses the issue of requirements change management in architectural design through traceability and reasoning. Part 2 "Tools and Techniques" presents approaches, tools, and techniques for bridging the gap between software requirements and architecture. Part 3 "Industrial Case Studies" then reports industrial experiences, while part 4 on "Emerging Issues" details advanced topics such as synthesizing architecture from requirements or the role of middleware in architecting for non-functional requirements. The final chapter is a conclusions chapter identifying key contributions and outstanding areas for future research and improvement of practice.The book is targeted at academic and industrial researchers in requirements engineering or software architecture. Graduate students specializing in these areas as well as advanced professionals in software development will also benefit from the results and experiences presented in this volume.

Software is pervasive in our lives. We are accustomed to dealing with the failures of much of that software - restarting an application is a very familiar solution. Such solutions are unacceptable when the software controls our cars, airplanes and medical devices or manages our private information. These applications must run without error. SPARK provides a means, based on mathematical proof, to guarantee that a program has no errors. SPARK is a formally defined programming language and a set of verification tools specifically designed to support the development of software used in high integrity applications. Using SPARK, developers can formally verify properties of their code such as information flow, freedom from runtime errors, functional correctness, security properties and safety properties. Written by two SPARK experts, this is the first introduction to the just-released 2014 version. It will help students and developers alike master the basic concepts for building systems with SPARK.

This book discusses Change Management Impact Analysis and how this method is used to analysis the risks and benefits of a change management initiative when it pertains to obtaining critical insight into how the change management program budget should be allotted. The process also offers useful indicators for what areas within the system should be monitored during the change management process. This book presents theoretical analysis of practical implications and surveys, along with analysis. It covers the functions aimed at identifying various stakeholders associated with the software such as requirement component, design component, and class component. The book talks about the interrelationship between the change and the effects on the rest of the system and dives deeper to include the critical role that the analysis places on the existing multiple functions such as estimating the development costs, the project overhead costs, cost for the modification of the system, and system strength or detecting errors in the system during the process. Case studies are also included to help researchers and practitioners to absorb the material presented. This book is useful to graduate students, researchers, academicians, institutions, and professionals that interested in exploring the areas of Impact Analysis.

The first edition of Exercises in Programming Style was honored as an ACM Notable Book and praised as "The best programming book of the decade." This new edition retains the same presentation but has been upgraded to Python 3, and there is a new section on neural network styles. Using a simple computational task (term frequency) to illustrate different programming styles, Exercises in Programming Style helps readers understand the various ways of writing programs and designing systems. It is designed to be used in conjunction with code provided on an online repository. The book complements and explains the raw code in a way that is accessible to anyone who regularly practices the art of programming. The book can also be used in advanced programming courses in computer science and software engineering programs. The book contains 40 different styles for writing the term frequency task. The styles are grouped into ten categories: historical, basic, function composition, objects and object interactions, reflection and metaprogramming, adversity, data-centric, concurrency, interactivity, and neural networks. The author states the constraints in each style and explains the example programs. Each chapter first presents the constraints of the style, next shows an example program, and then gives a detailed explanation of the code. Most chapters also have sections focusing on the use of the style in systems design as well as sections describing the historical context in which the programming style emerged.

The first edition of Exercises in Programming Style was honored as an ACM Notable Book and praised as "The best programming book of the decade." This new edition retains the same presentation but has been upgraded to Python 3, and there is a new section on neural network styles. Using a simple computational task (term frequency) to illustrate different programming styles, Exercises in Programming Style helps readers understand the various ways of writing programs and designing systems. It is designed to be used in conjunction with code provided on an online repository. The book complements and explains the raw code in a way that is accessible to anyone who regularly practices the art of programming. The book can also be used in advanced programming courses in computer science and software engineering programs. The book contains 40 different styles for writing the term frequency task. The styles are grouped into ten categories: historical, basic, function composition, objects and object interactions, reflection and metaprogramming, adversity, data-centric, concurrency, interactivity, and neural networks. The author states the constraints in each style and explains the example programs. Each chapter first presents the constraints of the style, next shows an example program, and then gives a detailed explanation of the code. Most chapters also have sections focusing on the use of the style in systems design as well as sections describing the historical context in which the programming style emerged.

This comprehensive book unveils the working relationship of blockchain and the fog/edge computing. The contents of the book have been designed in such a way that the reader will not only understand blockchain and fog/edge computing but will also understand their co-existence and their collaborative power to solve a range of versatile problems. The first part of the book covers fundamental concepts and the applications of blockchain-enabled fog and edge computing. These include: Internet of Things, Tactile Internet, Smart City; and E-challan in the Internet of Vehicles. The second part of the book covers security and privacy related issues of blockchain-enabled fog and edge computing. These include, hardware primitive based Physical Unclonable Functions; Secure Management Systems; security of Edge and Cloud in the presence of blockchain; secure storage in fog using blockchain; and using differential privacy for edge-based Smart Grid over blockchain. This book is written for students, computer scientists, researchers and developers, who wish to work in the domain of blockchain and fog/edge computing. One of the unique features of this book is highlighting the issues, challenges, and future research directions associated with Blockchain-enabled fog and edge computing paradigm. We hope the readers will consider this book a valuable addition in the domain of Blockchain and fog/edge computing.

This book is the follow-up of the Boost Volume I book and it has been written for software developers who use Boost C++ libraries to create flexible applications. We discuss approximately 20 advanced libraries that can be classified into the following major categories: Mathematics: special functions, statistical distributions, interval arithmetic and matrix algebra. Special data structures: date and time, circular buffer, UUID, dynamic bitsets, pool memory. TCP and UDP portable network programming using the software interface. Interprocess communication and shared memory programming models. Three chapters on graphs, graph algorithms and their implementation in Boost. The focus is hands-on and each library is discussed in detail and numerous working examples are given to get the reader up to speed as soon as possible. Each library is described in a step-by-step fashion and you can use the corresponding code as a basis for more advanced applications. These libraries are the ideal basis for new applications. We shall use them in Volume III of the current series when we discuss applications to engineering, science and computational finance. About the Authors Robert Demming is software designer, developer and trainer and he has been involved with software projects in the areas of optical technology, process control, CAD and order processing systems since 1993. He has a BSc degree in technical computerscience from Amsterdam Hogeschool. Daniel J. Duffy is founder of Datasim Education BV and has been working with C++ and its applications since 1989 and with software development since 1979. He is designer, algorithm builder and trainer. He has a PhD in numerical analysis from Trinity College, Dublin. One of the projects that he is involved in is applying the Boost libraries to computational finance."

The book begins with an introduction to software reliability, models and techniques. The book is an informative book covering the strategies needed to assess software failure behaviour and its quality, as well as the application of optimization tools for major managerial decisions related to the software development process. It features a broad range of topics including software reliability assessment and apportionment, optimal allocation and selection decisions and upgradations problems. It moves through a variety of problems related to the evolving field of optimization of software reliability engineering, including software release time, resource allocating, budget planning and warranty models, which are each explored in depth in dedicated chapters. This book provides a comprehensive insight into present-day practices in software reliability engineering, making it relevant to students, researchers, academics and practising consultants and engineers.

Developing secure software requires the integration of numerous methods and tools into the development process, and software design is based on shared expert knowledge, claims, and opinions. Empirical methods, including data analytics, allow extracting knowledge and insights from the data that organizations collect from their processes and tools, and from the opinions of the experts who practice these processes and methods. This book introduces the reader to the fundamentals of empirical research methods, and demonstrates how these methods can be used to hone a secure software development lifecycle based on empirical data and published best practices.

Guarantee the quality and consistency of your web APIs by implementing an automated testing process. In Testing Web APIs you will: Design and implement a web API testing strategy Set up a test automation suite Learn contract testing with Pact Facilitate collaborative discussions to test web API designs Perform exploratory tests Experiment safely in a downloadable API sandbox environment Testing Web APIs teaches you to plan and implement the perfect testing strategy for your web APIs. In it, you'll explore dozens of different testing activities to help you develop a custom testing regime for your projects. You'll learn to take a risk-driven approach to API testing, and build a strategy that goes beyond the basics of code and requirements coverage. about the technology To other developers, your API is the face of your application. Thorough, well-designed testing ensures that your APIs will perform as expected, every time. Impeccable API testing goes beyond the basics of code coverage, to encompass documentation and design that sends the right information to your third-party users. A robust testing strategy helps you avoid costly errors that can damage your revenue, your reputation, and your user's trust. about the book In Testing Web APIs you'll develop a diverse testing program that gets your whole team involved in ensuring quality. This practical book demystifies abstract strategic concepts by applying them to common API testing scenarios, revealing how these complex ideas work in the real world. It fully covers automation techniques like functional API automation, contract testing, and automated acceptance test-driven design that will save your team's time. You'll map the potential risks your API could face, and use those risks as a launching point for your testing activities. A good strategy has a mix of focuses, so you'll master a wide range of API testing techniques like exploratory testing and live testing of production code. A downloadable API sandbox lets you go hands-on and experiment in a safe environment. You'll soon be ready to implement a strategy that ensures API quality and makes testing a real asset to your team.

Practical Guidance on the Efficient Development of High-Quality Software Introduction to Software Engineering, Second Edition equips students with the fundamentals to prepare them for satisfying careers as software engineers regardless of future changes in the field, even if the changes are unpredictable or disruptive in nature. Retaining the same organization as its predecessor, this second edition adds considerable material on open source and agile development models. The text helps students understand software development techniques and processes at a reasonably sophisticated level. Students acquire practical experience through team software projects. Throughout much of the book, a relatively large project is used to teach about the requirements, design, and coding of software. In addition, a continuing case study of an agile software development project offers a complete picture of how a successful agile project can work. The book covers each major phase of the software development life cycle, from developing software requirements to software maintenance. It also discusses project management and explains how to read software engineering literature. Three appendices describe software patents, command-line arguments, and flowcharts.

Automatic biometrics recognition techniques are increasingly important in corporate and public security systems and have increased in methods due to rapid field development. This book discusses classic behavioral biometrics as well as collects the latest advances in techniques, theoretical approaches, and dynamic applications. This future-looking book is an important reference tool for researchers, practitioners, academicians, and technologists. While there are existing books that focus on physiological biometrics or algorithmic approaches deployed in biometrics, this book addresses a gap in the existing literature for a text that is solely dedicated to the topic of behavioral biometrics.

In the decade since the idea of adapting the evidence-based paradigm for software engineering was first proposed, it has become a major tool of empirical software engineering. Evidence-Based Software Engineering and Systematic Reviews provides a clear introduction to the use of an evidence-based model for software engineering research and practice. The book explains the roles of primary studies (experiments, surveys, case studies) as elements of an over-arching evidence model, rather than as disjointed elements in the empirical spectrum. Supplying readers with a clear understanding of empirical software engineering best practices, it provides up-to-date guidance on how to conduct secondary studies in software engineering-replacing the existing 2004 and 2007 technical reports. The book is divided into three parts. The first part discusses the nature of evidence and the evidence-based practices centered on a systematic review, both in general and as applying to software engineering. The second part examines the different elements that provide inputs to a systematic review (usually considered as forming a secondary study), especially the main forms of primary empirical study currently used in software engineering. The final part provides practical guidance on how to conduct systematic reviews (the guidelines), drawing together accumulated experiences to guide researchers and students in planning and conducting their own studies. The book includes an extensive glossary and an appendix that provides a catalogue of reviews that may be useful for practice and teaching.

The International Conference on Communications, Management, and Information Technology (ICCMIT'16) provides a discussion forum for scientists, engineers, educators and students about the latest discoveries and realizations in the foundations, theory, models and applications of systems inspired on nature, using computational intelligence methodologies, as well as in emerging areas related to the three tracks of the conference: Communication Engineering, Knowledge, and Information Technology. The best 25 papers to be included in the book will be carefully reviewed and selected from numerous submissions, then revised and expanded to provide deeper insight into trends shaping future ICT.

This is a how-to book for solving geometric problems robustly or error free in actual practice. The contents and accompanying source code are based on the feature requests and feedback received from industry professionals and academics who want both the descriptions and source code for implementations of geometric algorithms. The book provides a framework for geometric computing using several arithmetic systems and describes how to select the appropriate system for the problem at hand. Key Features: A framework of arithmetic systems that can be applied to many geometric algorithms to obtain robust or error-free implementations Detailed derivations for algorithms that lead to implementable code Teaching the readers how to use the book concepts in deriving algorithms in their fields of application The Geometric Tools Library, a repository of well-tested code at the Geometric Tools website, https://www.geometrictools.com, that implements the book concepts

This volume offers a systematic approach to creating and positioning reusable software components and products. The Domain Analysis methodology described in the book shows how to use commonality and variability analysis in studying the market, co-ordinating with competitors, engineering new products, and minimizing risks. Software engineers and network designers should learn how to analyze and define a "space of variability" on which new products can be based and positioned. Additionally, the book helps readers to understand how software products compare, how to market software reuse products, how to co-ordinate release of a product to profit from a competitor's release and pool groups of users, and how to maximize long-term marketing plans for your product. Real-world case studies illustrate applications of the methodologies described in the book, including "Sherlock", a method that binds domain analysis to market analysis and planning.

Designed to conform to the ISO/IEC standard 14143, the Common Software Measurement International Consortium (COSMIC) Function Point method has become the major estimation technique based on international standards for building software-intensive systems. COSMIC Function Points: Theory and Advanced Practices supplies a cutting-edge look at current and emerging practices in the international software measurement community. The editors have assembled an international panel of experts who detail the steps for measuring the functional size of software and developing project estimates with improved accuracy. They explain how to evaluate and compare systems to improve software reuse and development. Touching on the essential aspects of the next generation of functional size measurement methods, the book delineates best estimation and measurement practices as well as the development of benchmarks for quality improvement, including Six Sigma. This complete resource covers software measurement and estimation methods and practices for embedded systems, business applications, communications software, and control systems. Each chapter supplies the practical understanding required to create, implement, standardize, distribute, and adapt functional size measurement and project estimation to virtually any software context. Praise for: ... an excellent overview ... provides a strong knowledge background for both practitioners and researchers. ... With its broad background, it is useful for practically implementing and successfully adapting other functional sizing methods ... . The COSMIC function point techniques presented in this book will help you to implement, master, and improve your estimation process.-Christof Ebert, Managing Director, Vector Consulting Services