Computational Intelligence And Quantitative Software Engineering
Download Computational Intelligence And Quantitative Software Engineering full books in PDF, epub, and Kindle. Read online free Computational Intelligence And Quantitative Software Engineering ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Witold Pedrycz |
| Publisher | : Springer |
| Total Pages | : 212 |
| Release | : 2016-01-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3319259644 |
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.
| Author | : Witold Pedrycz |
| Publisher | : World Scientific |
| Total Pages | : 504 |
| Release | : 1998 |
| Genre | : Computers |
| ISBN | : 9789810235031 |
This unique volume is the first publication on software engineering and computational intelligence (CI) viewed as a synergistic interplay of neurocomputing, granular computation (including fuzzy sets and rough sets), and evolutionary methods. It presents a unified view of CI in the context of software engineering. The book addresses a number of crucial issues: what is CI, what role does it play in software development, how are CI elements built into successive phases of the software life cycle, and what is the role played by CI in quantifying fundamental features of software artifacts? With contributions from leading researchers and practitioners, the book provides the reader with a wealth of new concepts and approaches, complete algorithms, in-depth case studies, and thought-provoking exercises. The topics coverage include neurocomputing, granular as well as evolutionary computing, object-oriented analysis and design in software engineering. There is also an extensive bibliography.
| Author | : Meir Kalech |
| Publisher | : World Scientific |
| Total Pages | : 457 |
| Release | : 2021-06-15 |
| Genre | : Computers |
| ISBN | : 9811239932 |
Software is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE).Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges.This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering.Related Link(s)
| Author | : Roger Lee |
| Publisher | : Springer |
| Total Pages | : 202 |
| Release | : 2011-11-06 |
| Genre | : Technology & Engineering |
| ISBN | : 3642232027 |
The purpose of the 9th International Conference on Software Engineering Research, Management and Applications(SERA 2011) held on August 10-12, 2011 in Baltimore, Maryland was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas and research results about all aspects (theory, applications and tools) of computer and information sciences, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected 12 outstanding papers from SERA 2011, all of which you will find in this volume of Springer’s Studies in Computational Intelligence.
| Author | : Jonathan Lee |
| Publisher | : Springer |
| Total Pages | : 275 |
| Release | : 2013-11-11 |
| Genre | : Technology & Engineering |
| ISBN | : 3540364234 |
It is not an exaggeration to view Professor Lee's book," Software Engineer ing with Computational Intelligence," or SECI for short, as a pioneering contribution to software engineering. Breaking with the tradition of treat ing uncertainty, imprecision, fuzziness and vagueness as issues of peripheral importance, SECI moves them much closer to the center of the stage. It is ob vious, though still not widely accepted, that this is where these issues should be, since the real world is much too complex and much too ill-defined to lend itself to categorical analysis in the Cartesian spirit. As its title suggests, SECI employs the machineries of computational intel ligence (CI) and, more or less equivalently, soft computing (SC), to deal with the foundations and principal issues in software engineering. Basically, CI and SC are consortia of methodologies which collectively provide a body of con cepts and techniques for conception, design, construction and utilization of intelligent systems. The principal constituents of CI and SC are fuzzy logic, neurocomputing, evolutionary computing, probabilistic computing, chaotic computing and machine learning. The leitmotif of CI and SC is that, in general, better performance can be achieved by employing the constituent methodologies of CI and SC in combination rat her than in a stand-alone mode. In what follows, I will take the liberty of focusing my attention on fuzzy logic and fuzzy set theory, and on their roles in software engineering. But first, a couple of points of semantics which are in need of clarification.
| Author | : Zhang, Du |
| Publisher | : IGI Global |
| Total Pages | : 498 |
| Release | : 2006-10-31 |
| Genre | : Computers |
| ISBN | : 1591409438 |
"This book provides analysis, characterization and refinement of software engineering data in terms of machine learning methods. It depicts applications of several machine learning approaches in software systems development and deployment, and the use of machine learning methods to establish predictive models for software quality while offering readers suggestions by proposing future work in this emerging research field"--Provided by publisher.
| Author | : James F Peters |
| Publisher | : World Scientific |
| Total Pages | : 500 |
| Release | : 1998-12-24 |
| Genre | : Computers |
| ISBN | : 9814496022 |
This unique volume is the first publication on software engineering and computational intelligence (CI) viewed as a synergistic interplay of neurocomputing, granular computation (including fuzzy sets and rough sets), and evolutionary methods. It presents a unified view of CI in the context of software engineering.The book addresses a number of crucial issues: what is CI, what role does it play in software development, how are CI elements built into successive phases of the software life cycle, and what is the role played by CI in quantifying fundamental features of software artifacts?With contributions from leading researchers and practitioners, the book provides the reader with a wealth of new concepts and approaches, complete algorithms, in-depth case studies, and thought-provoking exercises. The topics coverage include neurocomputing, granular as well as evolutionary computing, object-oriented analysis and design in software engineering. There is also an extensive bibliography.
| Author | : Roger Lee |
| Publisher | : Springer |
| Total Pages | : 248 |
| Release | : 2013-05-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3319007386 |
This edited book presents scientific results of the 14th ACIS/IEEE International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2013), held in Honolulu, Hawaii, USA on July 1-3, 2013. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 17 outstanding papers from those papers accepted for presentation at the conference.
| Author | : Parma Nand |
| Publisher | : CRC Press |
| Total Pages | : 317 |
| Release | : 2023-02-10 |
| Genre | : Computers |
| ISBN | : 1000575926 |
This new volume explores the computational intelligence techniques necessary to carry out different software engineering tasks. Software undergoes various stages before deployment, such as requirements elicitation, software designing, software project planning, software coding, and software testing and maintenance. Every stage is bundled with a number of tasks or activities to be performed. Due to the large and complex nature of software, these tasks can become costly and error prone. This volume aims to help meet these challenges by presenting new research and practical applications in intelligent techniques in the field of software engineering. Computational Intelligence Applications for Software Engineering Problems discusses techniques and presents case studies to solve engineering challenges using machine learning, deep learning, fuzzy-logic-based computation, statistical modeling, invasive weed meta-heuristic algorithms, artificial intelligence, the DevOps model, time series forecasting models, and more.
| Author | : Taghi M. Khoshgoftaar |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 373 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1461504295 |
The constantly evolving technological infrastructure of the modem world presents a great challenge of developing software systems with increasing size, complexity, and functionality. The software engineering field has seen changes and innovations to meet these and other continuously growing challenges by developing and implementing useful software engineering methodologies. Among the more recent advances are those made in the context of software portability, formal verification· techniques, software measurement, and software reuse. However, despite the introduction of some important and useful paradigms in the software engineering discipline, their technological transfer on a larger scale has been extremely gradual and limited. For example, many software development organizations may not have a well-defined software assurance team, which can be considered as a key ingredient in the development of a high-quality and dependable software product. Recently, the software engineering field has observed an increased integration or fusion with the computational intelligence (Cl) field, which is comprised of primarily the mature technologies of fuzzy logic, neural networks, genetic algorithms, genetic programming, and rough sets. Hybrid systems that combine two or more of these individual technologies are also categorized under the Cl umbrella. Software engineering is unlike the other well-founded engineering disciplines, primarily due to its human component (designers, developers, testers, etc. ) factor. The highly non-mechanical and intuitive nature of the human factor characterizes many of the problems associated with software engineering, including those observed in development effort estimation, software quality and reliability prediction, software design, and software testing.
