Algorithms and Programming is primarily intended for use in a first-year undergraduate course in programming. It is structured in a problem-solution format that requires the student to think through the programming process, thus developing an understanding of the underlying theory. The book is easily readable by a student taking a basic introductory course in computer science as well as useful for a graduate-level course in the analysis of algorithms and/or compiler construction.

Each self-contained chapter presents classical and well-known problems supplemented by clear and in-depth explanations. The material covered includes such topics as combinatorics, sorting, searching, queues, grammar and parsing, selected well-known algorithms and much more. Students and teachers will find this both an excellent text for learning programming and a source of problems for a variety of courses.

Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language.The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages. Numeric Computation and Statistical Data Analysis on the Java Platform is a great choice for those who want to learn how statistical data analysis can be done using popular programming languages, who want to integrate data analysis algorithms in full-scale applications, and deploy such calculations on the web pages or computational servers regardless of their operating system. It is an excellent reference for scientific computations to solve real-world problems using a comprehensive stack of open-source Java libraries included in the DataMelt (DMelt) project and will be appreciated by many data-analysis scientists, engineers and students.

At present, there is a general consensus on the nature of learning programming, but there are different opinions on what forms an effective environment for it. It is generally recognized that the development of a mental model is a formidable task for the student and that learning programming is a complex activity that depends heavily on metacognitive skills. This book, based on a NATO workshop, presents both pure cognitive models and experimental learning environments, and discusses what characteristics can make a learning model effective, especially in relation to the learning environment (natural or computerized). The papers cover cognitive models related to different aspects of programming, classes of learners, and types of environment, and are organized in three groups: theoretical and empirical studies on understanding programming, environments for learning programming, and learning programming in school environments. Comprehension, design, construction, testing, debugging, and verification are recognized as interdependent skills, which require complicated analysis and may develop independently, and indifferent orders, in novices. This book shows that there is unlikely to be asingle path from novice to expert and that the structure of the final product (the program) may not constrain the process by which it comes into being as much as some would advocate.

With the growth of public and private data stores and the emergence of off-the-shelf data-mining technology, recommendation systems have emerged that specifically address the unique challenges of navigating and interpreting software engineering data.

This book collects, structures and formalizes knowledge on recommendation systems in software engineering. It adopts a pragmatic approach with an explicit focus on system design, implementation, and evaluation. The book is divided into three parts: "Part I - Techniques" introduces basics for building recommenders in software engineering, including techniques for collecting and processing software engineering data, but also for presenting recommendations to users as part of their workflow."Part II - Evaluation" summarizes methods and experimental designs for evaluating recommendations in software engineering."Part III - Applications" describes needs, issues and solution concepts involved in entire recommendation systems for specific software engineering tasks, focusing on the engineering insights required to make effective recommendations. The book is complemented by the webpage rsse.org/book, which includes free supplemental materials for readers of this book and anyone interested in recommendation systems in software engineering, including lecture slides, data sets, source code, and an overview of people, groups, papers and tools with regard to recommendation systems in software engineering.

The book is particularly well-suited for graduate students and researchers building new recommendation systems for software engineering applications or in other high-tech fields. It may also serve as the basis for graduate courses on recommendation systems, applied data mining or software engineering. Software engineering practitioners developing recommendation systems or similar applications with predictive functionality will also benefit from the broad spectrum of topics covered."

Developing correct and efficient software is far more complex for parallel and distributed systems than it is for sequential processors. Some of the reasons for this added complexity are: the lack of a universally acceptable parallel and distributed programming paradigm, the criticality of achieving high performance, and the difficulty of writing correct parallel and distributed programs. These factors collectively influence the current status of parallel and distributed software development tools efforts. Tools and Environments for Parallel and Distributed Systems addresses the above issues by describing working tools and environments, and gives a solid overview of some of the fundamental research being done worldwide. Topics covered in this collection are: mainstream program development tools, performance prediction tools and studies; debugging tools and research; and nontraditional tools. Audience: Suitable as a secondary text for graduate level courses in software engineering and parallel and distributed systems, and as a reference for researchers and practitioners in industry.

In "Physical Unclonable Functions in Theory and Practice," the authorspresent an in-depth overview ofvarious topics concerning PUFs, providing theoretical background and application details. This book concentrates on the practical issues of PUF hardware design, focusing on dedicated microelectronic PUF circuits.

Additionally, the authors discuss the whole process of circuit design, layout and chip verification. The book also offers coverage of: Different published approaches focusing on dedicated microelectronic PUF circuits Specification of PUF circuits General design issues Minimizing error rate from the circuit s perspective Transistor modeling issues of Montecarlo mismatch simulation and solutions Examples of PUF circuits including an accurate description of the circuits and testing/measurement resultsDifferent error rate reducing pre-selection techniques

This monographgives insight into PUFs in general and provides knowledge in the field of PUF circuit design and implementation. It could be of interest for all circuit designers confronted with PUF design, and also for professionals and students being introduced to the topic."

HIS BOOK CONTAINS a most comprehensive text that presents syntax-directed and compositional methods for the formal veri?- T cation of programs. The approach is not language-bounded in the sense that it covers a large variety of programming models and features that appear in most modern programming languages. It covers the classes of - quential and parallel, deterministic and non-deterministic, distributed and object-oriented programs. For each of the classes it presents the various c- teria of correctness that are relevant for these classes, such as interference freedom, deadlock freedom, and appropriate notions of liveness for parallel programs. Also, special proof rules appropriate for each class of programs are presented. In spite of this diversity due to the rich program classes cons- ered, there exist a uniform underlying theory of veri?cation which is synt- oriented and promotes compositional approaches to veri?cation, leading to scalability of the methods. The text strikes the proper balance between mathematical rigor and - dactic introduction of increasingly complex rules in an incremental manner, adequately supported by state-of-the-art examples. As a result it can serve as a textbook for a variety of courses on di?erent levels and varying durations. It can also serve as a reference book for researchers in the theory of veri?- tion, in particular since it contains much material that never before appeared in book form. This is specially true for the treatment of object-oriented p- grams which is entirely novel and is strikingly elegant.

Business applications are designed using profound knowledge about the business domain, such as domain objects, fundamental domain-related principles, and domain patterns. Nonetheless, the pattern community's ideas for software engineering have not impacted at the application level, they are still mostly used for technical problems.

This book takes exactly this step: it shows you how to apply the pattern ideas in business applications and presents more than 20 structural and behavioral business patterns that use the REA (resources, events, agents) pattern as a common backbone. If you are a developer working on business frameworks, you can use the patterns presented to derive the right abstractions (e.g., business objects) and to design and ensure that the meta-rules (e.g., process patterns) are followed by the developers of the actual applications. And if you are an application developer, you can use these patterns to design your business application, to ensure that it does not violate the domain rules, and to adapt the application to changing requirements without the need to change the overall architecture. As with patterns in general, this approach allows for both more flexible and more solid software architectures and hence better software quality.

"It's a great book, marvelous in breadth and depth. An impressive achievement. I particularly liked the modeling handbook examples." Bob Haugen, Business Technology Consultant and Contributor to REA standardization in ISO, UN/CEFACT and ebXML, UK

"I enjoyed reading it very much, it gave many new insights into REA and its applications." Paul Johannesson, Stockholm University and Royal Institute of Technology, Sweden

"This book by Pavel Hruby is destined to become a landmark in business modeling. Pavel heralds the replacement of traditional workflow-oriented modeling with a new breed of approaches that focus on delivering change-resilient and highly reusable business models. I highly recommend this book to you " Krzysztof Czarnecki, University of Waterloo, Canada

This volume contains several surveys focused on the ideas of approximate solutions, well-posedness and stability of problems in scalar and vector optimization, game theory and calculus of variations. These concepts are of particular interest in many fields of mathematics. The idea of stability goes back at least to J. Hadamard who introduced it in the setting of differential equations; the concept of well-posedness for minimum problems is more recent (the mid-sixties) and originates with A.N. Tykhonov. It turns out that there are connections between the two properties in the sense that a well-posed problem which, at least in principle, is "easy to solve," has a solution set that does not vary too much under perturbation of the data of the problem, i.e. it is "stable." These themes have been studied in depth for minimum problems and now we have a general picture of the related phenomena in this case. But, of course, the same concepts can be studied in other more complicated situations as, e.g. vector optimization, game theory and variational inequalities. Let us mention that in several of these new areas there is not even a unique idea of what should be called approximate solution, and the latter is at the basis of the definition of well posed problem."

This book explores coordination within and between teams in the context of large-scale agile software development, providing readers a deeper understanding of how coordinated action between teams is achieved in multiteam systems. An exploratory multiple case study with five multiteam systems and a total of 66 interviewees from development teams at SAP SE is presented and analyzed. In addition, the book explores stereotypes of coordination in large-scale agile settings and shares new perspectives on integrating conditions for coordination. No previous study has researched this topic with a similar data set, consisting of insights from professional software development teams. As such, the book will be of interest to all researchers and practitioners whose work involves software product development across several teams.

Embedded computing systems play an important and complex role in the functionality of electronic devices. With our daily routines becoming more reliant on electronics for personal and professional use, the understanding of these computing systems is crucial. Embedded Computing Systems: Applications, Optimization, and Advanced Design brings together theoretical and technical concepts of intelligent embedded control systems and their use in hardware and software architectures. By highlighting formal modeling, execution models, and optimal implementations, this reference source is essential for experts, researchers, and technical supporters in the industry and academia.

This book represents the refereed proceedings of the Ninth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Warsaw (Poland) in August 2010. These biennial conferences are major events for Monte Carlo and the premiere event for quasi-Monte Carlo research. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. The reader will be provided with information on latest developments in these very active areas. The book is an excellent reference for theoreticians and practitioners interested in solving high-dimensional computational problems arising, in particular, in finance and statistics.

Computer Aided Software Engineering brings together in one place important contributions and up-to-date research results in this important area. Computer Aided Software Engineering serves as an excellent reference, providing insight into some of the most important research issues in the field.

This book contains leading survey papers on the various aspects of Abduction, both logical and numerical approaches. Abduction is central to all areas of applied reasoning, including artificial intelligence, philosophy of science, machine learning, data mining and decision theory, as well as logic itself.

3D Virtual Applications: Applications with Virtual Inhabited 3D Worlds deals with the use of virtual inhabited 3D spaces in different domains of society. (Other volumes deal with interaction, production methodology and space.) From focusing on virtual reality (a reality into which users and objects from the real world should be moved) we are increasingly focusing on augmented reality (i.e. on moving computers out into the reality of real users, objects and activities). This book deals with the use of virtual inhabited 3D spaces in both contexts. Based on the structuring of the application domains, this book looks at the use of VR and augmented reality in the following major application domains:

- Production oriented applications - use of VR and augmented reality for control of complex production plants, for navigation support (ships, cars, aeroplanes) and for support of collaborative work processes

- Communication support applications - virtual spaces are used for supporting communication in learning environments and for support of organisational communication. Also virtual spaces are used for supporting the navigation of people in public spaces, i.e. as maps, planning tools

- Scientific applications - use of 3D models for medical research; use of dynamic models for representation of abstract concepts and ideas (data-mining applications); use of dynamic 3D models for simulating biological or social processes

- Artistic and cultural applications - the construction of stages representing concepts and/or emotions

Graph Separators with Applications is devoted to techniques for obtaining upper and lower bounds on the sizes of graph separators - upper bounds being obtained via decomposition algorithms. The book surveys the main approaches to obtaining good graph separations, while the main focus of the book is on techniques for deriving lower bounds on the sizes of graph separators. This asymmetry in focus reflects our perception that the work on upper bounds, or algorithms, for graph separation is much better represented in the standard theory literature than is the work on lower bounds, which we perceive as being much more scattered throughout the literature on application areas. Given the multitude of notions of graph separator that have been developed and studied over the past (roughly) three decades, there is a need for a central, theory-oriented repository for the mass of results. The need is absolutely critical in the area of lower-bound techniques for graph separators, since these techniques have virtually never appeared in articles having the word separator' or any of its near-synonyms in the title. Graph Separators with Applications fills this need.

Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by well known researchers in the field, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing.
Managing and Mining Graph Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This volume is also suitable as a reference book for advanced-level database students in computer science and engineering.

Graph theory is a specific concept that has numerous applications throughout many industries. Despite the advancement of this technique, graph theory can still yield ambiguous and imprecise results. In order to cut down on these indeterminate factors, neutrosophic logic has emerged as an applicable solution that is gaining significant attention in solving many real-life decision-making problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistency, and indeterminacy. However, empirical research on this specific graph set is lacking. Neutrosophic Graph Theory and Algorithms is a collection of innovative research on the methods and applications of neutrosophic sets and logic within various fields including systems analysis, economics, and transportation. While highlighting topics including linear programming, decision-making methods, and homomorphism, this book is ideally designed for programmers, researchers, data scientists, mathematicians, designers, educators, researchers, academicians, and students seeking current research on the various methods and applications of graph theory.

Object-oriented database management systems (OODBMS) are used to imple ment and maintain large object databases on persistent storage. Regardless whether the underlying database model follows the object-oriented, the rela tional or the object-relational paradigm, a key feature of any DBMS product is content based access to data sets. On the one hand this feature provides user-friendly query interfaces based on predicates to describe the desired data. On the other hand it poses challenging questions regarding DBMS design and implementation as well as the application development process on top of the DBMS. The reason for the latter is that the actual query performance depends on a technically meaningful use of access support mechanisms. In particular, if chosen and applied properly, such a mechanism speeds up the execution of predicate based queries. In the object-oriented world, such queries may involve arbitrarily complex terms referring to inheritance hierarchies and aggregation paths. These features are attractive at the application level, however, they increase the complexity of appropriate access support mechanisms which are known to be technically non-trivial in the relational world."

The software product line strategy has enabled many organizations to improve productivity, reduce time-to-market, and address both mass- and niche markets. A successful product line organization achieves strategic levels of architectural reuse.

The topics in this book cover research related to the most important practices in a product line organization. The contributions provide experience-based knowledge about the domain and application engineering, the modeling and management of variability, and the design and use of tools to support the management of product line related knowledge. Kakola and Duenas have grouped them into five parts corresponding to the main areas of software product line engineering: product line management, product line requirements engineering, product line architecture, product line testing, and specific product line engineering issues. They ensured maximum coherence and cross-referencing throughout the book, imposing a common terminology and carefully integrating all chapters. The result is a valuable and enduring resource for researchers in both industry and academia who will also find many pointers for future research and implementation strategies. In addition, systems and software professionals, and technology managers aspiring to fully leverage the product line strategy will also benefit from many pertinent development details.

"This volume is a valuable resource for researchers wishing to move the product line strategy forward and for those charged with translating state-of-the-art ideas into state-of-the-practice processes and activities."

From the Foreword by John D. McGregor, Clemson University, USA

Updated for Excel 2021 and based on the bestselling editions from previous versions, Excel 2021 / Microsoft 365 Programming by Example is a practical, how-to book on Excel programming, suitable for readers already proficient with the Excel user interface. If you are looking to automate Excel routine tasks, this book will progressively introduce you to programming concepts via numerous illustrated hands-on exercises. More advanced topics are demonstrated via custom projects. From recording and editing a macro and writing VBA code from scratch to programming the Ribbon interface and working with XML documents, this book takes you on a programming journey that will change the way you work with Excel. The book provides information on performing automatic operations on files, folders, and other Microsoft Office applications. It also covers proper use of event procedures, testing and debugging, and guides you through programming more advanced Excel features, such as working with VBA classes and raising your own events in standalone class modules. Includes companion files with source code, hands-on projects, and figures.

This book provides an effective overview of the state-of-the art in software engineering, with a projection of the future of the discipline. It includes 13 papers, written by leading researchers in the respective fields, on important topics like model-driven software development, programming language design, microservices, software reliability, model checking and simulation. The papers are edited and extended versions of the presentations at the PAUSE symposium, which marked the completion of 14 years of work at the Chair of Software Engineering at ETH Zurich. In this inspiring context, some of the greatest minds in the field extensively discussed the past, present and future of software engineering. It guides readers on a voyage of discovery through the discipline of software engineering today, offering unique food for thought for researchers and professionals, and inspiring future research and development.

As information technologies become increasingly distributed and accessible to larger number of people and as commercial and government organizations are challenged to scale their applications and services to larger market shares, while reducing costs, there is demand for software methodologies and appli- tions to provide the following features: Richer application end-to-end functionality; Reduction of human involvement in the design and deployment of the software; Flexibility of software behaviour; and Reuse and composition of existing software applications and systems in novel or adaptive ways. When designing new distributed software systems, the above broad requi- ments and their translation into implementations are typically addressed by partial complementarities and overlapping technologies and this situation gives rise to significant software engineering challenges. Some of the challenges that may arise are: determining the components that the distributed applications should contain, organizing the application components, and determining the assumptions that one needs to make in order to implement distributed scalable and flexible applications, etc.