Computational Intelligence in Software Quality Assurance

Computational Intelligence in Software Quality Assurance PDF Author: Scott Dick
Publisher: World Scientific
ISBN: 9812703470
Category : Computers
Languages : en
Pages : 199

Get Book

Book Description
Software systems surround us. Software is a critical component in everything from the family car through electrical power systems to military equipment. As software plays an ever-increasing role in our lives and livelihoods, the quality of that software becomes more and more critical. However, our ability to deliver high-quality software has not kept up with those increasing demands. The economic fallout is enormous; the US economy alone is losing over US$50 billion per year due to software failures. This book presents new research into using advanced artificial intelligence techniques to guide software quality improvements. The techniques of chaos theory and data mining are brought to bear to provide new insights into the software development process. Written for researchers and practitioners in software engineering and computational intelligence, this book is a unique and important bridge between these two fields.

Computational Intelligence in Software Quality Assurance

Computational Intelligence in Software Quality Assurance PDF Author: Scott Dick
Publisher: World Scientific
ISBN: 9812561722
Category : Technology & Engineering
Languages : en
Pages : 202

Get Book

Book Description
Software systems surround us. Software is a critical component in everything from the family car through electrical power] systems to military equipment. As software ploys an ever-increasing role in our lives and livelihoods, the quality of that software becomes more and more critical. However, our ability to deliver high-quality software has not kept up with those increasing demands. The economic fallout is enormous; the US economy alone is losing over US$50 billion per year due to software failures. This book presents new research into using advanced artificial intelligence techniques to guide software quality improvements. The techniques of chaos theory and data mining arc brought to bear to provide new insights into the software development process. Written for researchers and practitioners in software engineering and computational intelligence, this book is a unique and important bridge between these two fields.

The Future of Software Quality Assurance

The Future of Software Quality Assurance PDF Author: Stephan Goericke
Publisher: Springer Nature
ISBN: 3030295095
Category : Computers
Languages : en
Pages : 272

Get Book

Book Description
This open access book, published to mark the 15th anniversary of the International Software Quality Institute (iSQI), is intended to raise the profile of software testers and their profession. It gathers contributions by respected software testing experts in order to highlight the state of the art as well as future challenges and trends. In addition, it covers current and emerging technologies like test automation, DevOps, and artificial intelligence methodologies used for software testing, before taking a look into the future. The contributing authors answer questions like: "How is the profession of tester currently changing? What should testers be prepared for in the years to come, and what skills will the next generation need? What opportunities are available for further training today? What will testing look like in an agile world that is user-centered and fast-paced? What tasks will remain for testers once the most important processes are automated?" iSQI has been focused on the education and certification of software testers for fifteen years now, and in the process has contributed to improving the quality of software in many areas. The papers gathered here clearly reflect the numerous ways in which software quality assurance can play a critical role in various areas. Accordingly, the book will be of interest to both professional software testers and managers working in software testing or software quality assurance.

Artificial Intelligence Methods in Software Testing

Artificial Intelligence Methods in Software Testing PDF Author: Mark Last
Publisher: World Scientific
ISBN: 9814482609
Category : Computers
Languages : en
Pages : 220

Get Book

Book Description
An inadequate infrastructure for software testing is causing major losses to the world economy. The characteristics of software quality problems are quite similar to other tasks successfully tackled by artificial intelligence techniques. The aims of this book are to present state-of-the-art applications of artificial intelligence and data mining methods to quality assurance of complex software systems, and to encourage further research in this important and challenging area. Contents:Fuzzy Cause–Effect Models of Software Testing (W Pedrycz & G Vukovich)Black-Box Testing with Info-Fuzzy Networks (M Last & M Friedman)Automated GUI Regression Testing Using AI Planning (A M Memon)Test Set Generation and Reduction with Artificial Neural Networks (P Saraph et al.)Three-Group Software Quality Classification Modeling Using an Automated Reasoning Approach (T M Khoshgoftaar & N Seliya)Data Mining with Resampling in Software Metrics Databases (S Dick & A Kandel) Readership: Students, researchers and professionals in computer science, information systems, software testing and data mining. Keywords:Artificial Intelligence;Data Mining;Software Testing;System Testing;Software Quality;Software Engineering;Software MetricsKey Features:Coverage of novel methods for software testing and software quality assuranceIntroduction to state-of-the-art data mining models and techniquesAnalyses of new and promising application domains of artificial intelligence and data mining in software quality engineeringContributions from leading authors in the fields of software engineering and data mining

Computational Intelligence in Software Modeling

Computational Intelligence in Software Modeling PDF Author: Vishal Jain
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110709244
Category : Computers
Languages : en
Pages : 216

Get Book

Book Description
Researchers, academicians and professionals expone in this book their research in the application of intelligent computing techniques to software engineering. As software systems are becoming larger and complex, software engineering tasks become increasingly costly and prone to errors. Evolutionary algorithms, machine learning approaches, meta-heuristic algorithms, and others techniques can help the effi ciency of software engineering.

Intelligent Systems and Applications

Intelligent Systems and Applications PDF Author: Kohei Arai
Publisher: Springer Nature
ISBN: 303082196X
Category : Technology & Engineering
Languages : en
Pages : 858

Get Book

Book Description
This book presents Proceedings of the 2021 Intelligent Systems Conference which is a remarkable collection of chapters covering a wider range of topics in areas of intelligent systems and artificial intelligence and their applications to the real world. The conference attracted a total of 496 submissions from many academic pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer-review process. Of the total submissions, 180 submissions have been selected to be included in these proceedings. As we witness exponential growth of computational intelligence in several directions and use of intelligent systems in everyday applications, this book is an ideal resource for reporting latest innovations and future of AI. The chapters include theory and application on all aspects of artificial intelligence, from classical to intelligent scope. We hope that readers find the book interesting and valuable; it provides the state-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of the future research.

Computational Intelligence in Software Engineering

Computational Intelligence in Software Engineering PDF Author: Witold Pedrycz
Publisher: World Scientific
ISBN: 9789810235031
Category : Computers
Languages : en
Pages : 504

Get Book

Book Description
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.

Computational Intelligence in Software Modeling

Computational Intelligence in Software Modeling PDF Author: Vishal Jain
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110709341
Category : Computers
Languages : en
Pages : 282

Get Book

Book Description
Researchers, academicians and professionals expone in this book their research in the application of intelligent computing techniques to software engineering. As software systems are becoming larger and complex, software engineering tasks become increasingly costly and prone to errors. Evolutionary algorithms, machine learning approaches, meta-heuristic algorithms, and others techniques can help the effi ciency of software engineering.

Software Engineering with Computational Intelligence

Software Engineering with Computational Intelligence PDF Author: Taghi M. Khoshgoftaar
Publisher: Springer Science & Business Media
ISBN: 1461504295
Category : Computers
Languages : en
Pages : 373

Get Book

Book Description
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.

Reliability and Statistical Computing

Reliability and Statistical Computing PDF Author: Hoang Pham
Publisher: Springer Nature
ISBN: 3030434125
Category : Technology & Engineering
Languages : en
Pages : 325

Get Book

Book Description
This book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems. Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.