Computational Intelligence and Quantitative Software Engineering / edited by Witold Pedrycz, Giancarlo Succi, Alberto Sillitti
Contributor(s): SpringerLink (Online service)
| Pedrycz, Witold, editor literario
| Succi, Giancarlo, editor literario
| Sillitti, Alberto., editor literario
Material type:
E-bookSeries: (Studies in Computational Intelligence, 1860-949X; 617).Publisher: Cham : Springer International Publishing, 2016Edition: 1st ed.Description: 1 recurso en línea (IX, 207 páginas) : 41 ilustraciones, 26 ilustraciones en color.ISBN: 9783319259642.Subject: Ingeniería del software
Abstract: In a down-to-the earth manner, the volume lucidly presents how the fundamental concepts, methodology, and algorithms of Computational Intelligence are efficiently exploited in Software Engineering and opens up a novel and promising avenue of a comprehensive analysis and advanced design of software artifacts. It shows how the paradigm and the best practices of Computational Intelligence can be creatively explored to carry out comprehensive software requirement analysis, support design, testing, and maintenance. Software Engineering is an intensive knowledge-based endeavor of inherent human-centric nature, which profoundly relies on acquiring semiformal knowledge and then processing it to produce a running system. The knowledge spans a wide variety of artifacts, from requirements, captured in the interaction with customers, to design practices, testing, and code management strategies, which rely on the knowledge of the running system. This volume consists of contributions written by widely acknowledged experts in the field who reveal how the Software Engineering benefits from the key foundations and synergistically existing technologies of Computational Intelligence being focused on knowledge representation, learning mechanisms, and population-based global optimization strategies. This book can serve as a highly useful reference material for researchers, software engineers and graduate students and senior undergraduate students in Software Engineering and its sub-disciplines, Internet engineering, Computational Intelligence, management, operations research, and knowledge-based systems.
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
|
Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | Q342 .C667 2016 EB (Browse shelf(Opens below)) | .i11588391 | Acceso electrónico | eBOOK .i11588391 |
Browsing Madrid Digital shelves, Shelving location: Acceso Electrónico (UEM) Close shelf browser (Hides shelf browser)
| Q342 .C667 2015 EB Computational Intelligence Applications in Modeling and Control | Q342 .C667 2015 EB Complex System Modelling and Control Through Intelligent Soft Computations | Q342 .C667 2016 EB Computer and Information Science 2015 | Q342 .C667 2016 EB Computational Intelligence and Quantitative Software Engineering | Q342 .C667 2016 EB Computational Sustainability | Q342 .C667 2016 EB Computational Intelligence and Intelligent Systems : 7th International Symposium, ISICA 2015, Guangzhou, China, November 21-22, 2015, Revised Selected Papers | Q342 .C667 2017 EB Computational intelligence in wireless sensor networks : recent advances and future challenges |
In a down-to-the earth manner, the volume lucidly presents how the fundamental concepts, methodology, and algorithms of Computational Intelligence are efficiently exploited in Software Engineering and opens up a novel and promising avenue of a comprehensive analysis and advanced design of software artifacts. It shows how the paradigm and the best practices of Computational Intelligence can be creatively explored to carry out comprehensive software requirement analysis, support design, testing, and maintenance. Software Engineering is an intensive knowledge-based endeavor of inherent human-centric nature, which profoundly relies on acquiring semiformal knowledge and then processing it to produce a running system. The knowledge spans a wide variety of artifacts, from requirements, captured in the interaction with customers, to design practices, testing, and code management strategies, which rely on the knowledge of the running system. This volume consists of contributions written by widely acknowledged experts in the field who reveal how the Software Engineering benefits from the key foundations and synergistically existing technologies of Computational Intelligence being focused on knowledge representation, learning mechanisms, and population-based global optimization strategies. This book can serve as a highly useful reference material for researchers, software engineers and graduate students and senior undergraduate students in Software Engineering and its sub-disciplines, Internet engineering, Computational Intelligence, management, operations research, and knowledge-based systems.
There are no comments on this title.