Models and Tools for Managing Development Processes

Models and Tools for Managing Development Processes Review

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Models and Tools for Managing Development Processes Feature

This book is devoted to models and tools for managing development processes in the fields of software engineering and mechanical and chemical engineering. The author evaluates the state of the art in the area and presents an integrated approach addressing the limitations of the presently available tools and systems. The models introduced for managing development processes cover products, activities, and resources in a systematic and coherent way; moreover, the models are designed to cope with the dynamics of the development processes. The tools and the management system developed by the author provide customized environments for different classes of users. The management environment supports managers in coordinating managerial activities; developers use the work environment in order to perform technical activities; finally, the modeling environment is used to adapt the management system to specific application domains.

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Models in Software Engineering: Workshops and Symposia at MODELS 2008, Toulouse, France, September 28

Models in Software Engineering: Workshops and Symposia at MODELS 2008, Toulouse, France, September 28 Review

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Models in Software Engineering: Workshops and Symposia at MODELS 2008, Toulouse, France, September 28 Feature

This book constitutes a collection of the best papers selected from the 12 workshops and 3 tutorials held in conjunction with MODELS 2008, the 11th International Conference on Model Driven Engineering Languages and Systems, in Toulouse, France, September 28 - October 3, 2008.

The contributions are organized within the volume according to the workshops at which they were presented: Model Based Architecting and Construction of Embedded Systems (ACES-MB); Challenges in Model Driven Software Engineering (CHAMDE); Empirical Studies of Model Driven Engineering (ESMDA); Models@runtime; Model Co-evolution and Consistency Management (MCCM); Model-Driven Web Engineering (MDWE); Modeling Security (MODSEC); Model-Based Design of Trustworthy Health Information Systems (MOTHIS); Non-functional System Properties in Domain Specific Modeling Languages (NFPin DSML); OCL Tools: From Implementation to Evaluation and Comparison (OCL); Quality in Modeling (QIM); and Transforming and Weaving Ontologies and Model Driven Engineering (TWOMDE). Each section includes a summary of the workshop. The last three sections contain selected papers from the Doctoral Symposium, the Educational Symposium and the Research Project Symposium, respectively.

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Level Crossing Methods in Stochastic Models (International Series in Operations Research & Management Science)

Level Crossing Methods in Stochastic Models (International Series in Operations Research & Management Science) Review

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Level Crossing Methods in Stochastic Models (International Series in Operations Research & Management Science) Feature

Since its inception in 1974, the level crossing approach for analyzing a large class of stochastic models has become increasingly popular among researchers. This volume traces the evolution of level crossing theory for obtaining probability distributions of state variables and demonstrates solution methods in a variety of stochastic models including: queues, inventories, dams, renewal models, counter models, pharmacokinetics, and the natural sciences. Results for both steady-state and transient distributions are given, and numerous examples help the reader apply the method to solve problems faster, more easily, and more intuitively. The book includes introductory material for readers new to the area, as well as advanced material for experienced users of the method, highlighting its usefulness for analyzing a broad class of models and illustrating its flexibility and adaptivity. The concepts, techniques, examples, applications and theoretical results in this book may suggest potentially new theory and new applications. The result is an essential resource for researchers, students, and professionals in operations research, management science, engineering, applied probability, statistics, actuarial science, mathematics, and the natural sciences.

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Metrics For Software Conceptual Models

Metrics For Software Conceptual Models Review

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Metrics For Software Conceptual Models Feature

The idea that "measuring quality is the key to developing high-quality software systems" is gaining relevance. Moreover, it is widely recognised that the key to obtaining better software systems is to measure the quality characteristics of early artefacts, produced at the conceptual modelling phase. Therefore, improving the quality of conceptual models is a major step towards the improvement of software system development. Since the 1970s, software engineers had been proposing high quantities of metrics for software products, processes and resources but had not been paying any special attention to conceptual modelling. By the mid-1990s, however, the need for metrics for conceptual modelling had emerged. This book provides an overview of the most relevant existing proposals of metrics for conceptual models, covering conceptual models for both products and processes.

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Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software

Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software Review

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Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software Feature

This volume systematically details both the basic principles and new developments in Data Envelopment Analysis (DEA), offering a solid understanding of the methodology, its uses, and its potential. New material in this edition includes coverage of recent developments that have greatly extended the power and scope of DEA and have lead to new directions for research and DEA uses. Each chapter accompanies its developments with simple numerical examples and discussions of actual applications. The first nine chapters cover the basic principles of DEA, while the final seven chapters provide a more advanced treatment.

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Metrics and Models in Software Quality Engineering (2nd Edition)

Metrics and Models in Software Quality Engineering (2nd Edition) Review

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Metrics and Models in Software Quality Engineering (2nd Edition) Feature

Our society has become increasingly reliant on software in the past decade; businesses have learned that measuring the effectiveness of software projects can impact the bottom line; and quality is no longer an advantage in the software marketplace (it is a necessity). For these reasons, the demand for quality in software engineering has taken center stage in the twenty-first century. In this new edition, Stephen Kan presents a thoroughly updated overview and implementation guide for software engineers faced with the challenge of ensuring quality. The book balances theory, techniques, and real-life examples to provide practical guidelines in the practice of quality. Although there are equations and formulas presented, the book's focus remains on helping the reader understand and apply the metrics and models. With this book as a map, readers can navigate through the complex field of quality, and benefit their organization by improving their processes and products.

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