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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 CauseOCoEffect 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."
Book Synopsis Artificial Intelligence Methods in Software Testing by : Horst Bunke
Download or read book Artificial Intelligence Methods in Software Testing written by Horst Bunke and published by World Scientific. This book was released on 2004 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 CauseOCoEffect 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."
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.
Book Synopsis The Future of Software Quality Assurance by : Stephan Goericke
Download or read book The Future of Software Quality Assurance written by Stephan Goericke and published by Springer Nature. This book was released on 2019-11-19 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 for Optimization of the Software Testing Process: With Practical Examples and Exercises presents different AI-based solutions for overcoming the uncertainty found in many initial testing problems. The concept of intelligent decision making is presented as a multi-criteria, multi-objective undertaking. The book provides guidelines on how to manage diverse types of uncertainty with intelligent decision-making that can help subject matter experts in many industries improve various processes in a more efficient way. As the number of required test cases for testing a product can be large (in industry more than 10,000 test cases are usually created). Executing all these test cases without any particular order can impact the results of the test execution, hence this book fills the need for a comprehensive resource on the topics on the how's, what's and whys. To learn more about Elsevier’s Series, Uncertainty, Computational Techniques and Decision Intelligence, please visit this link: https://www.elsevier.com/books-and-journals/book-series/uncertainty-computational-techniques-and-decision-intelligence Presents one of the first empirical studies in the field, contrasting theoretical assumptions on innovations in a real industrial environment with a large set of use cases from developed and developing testing processes at various large industries Explores specific comparative methodologies, focusing on developed and developing AI-based solutions Serves as a guideline for conducting industrial research in the artificial intelligence and software testing domain Explains all proposed solutions through real industrial case studies
Book Synopsis Artificial Intelligence Methods for Optimization of the Software Testing Process by : Sahar Tahvili
Download or read book Artificial Intelligence Methods for Optimization of the Software Testing Process written by Sahar Tahvili and published by Academic Press. This book was released on 2022-07-21 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence Methods for Optimization of the Software Testing Process: With Practical Examples and Exercises presents different AI-based solutions for overcoming the uncertainty found in many initial testing problems. The concept of intelligent decision making is presented as a multi-criteria, multi-objective undertaking. The book provides guidelines on how to manage diverse types of uncertainty with intelligent decision-making that can help subject matter experts in many industries improve various processes in a more efficient way. As the number of required test cases for testing a product can be large (in industry more than 10,000 test cases are usually created). Executing all these test cases without any particular order can impact the results of the test execution, hence this book fills the need for a comprehensive resource on the topics on the how's, what's and whys. To learn more about Elsevier’s Series, Uncertainty, Computational Techniques and Decision Intelligence, please visit this link: https://www.elsevier.com/books-and-journals/book-series/uncertainty-computational-techniques-and-decision-intelligence Presents one of the first empirical studies in the field, contrasting theoretical assumptions on innovations in a real industrial environment with a large set of use cases from developed and developing testing processes at various large industries Explores specific comparative methodologies, focusing on developed and developing AI-based solutions Serves as a guideline for conducting industrial research in the artificial intelligence and software testing domain Explains all proposed solutions through real industrial case studies
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)
Book Synopsis Artificial Intelligence Methods For Software Engineering by : Meir Kalech
Download or read book Artificial Intelligence Methods For Software Engineering written by Meir Kalech and published by World Scientific. This book was released on 2021-06-15 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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)
First Published in 1990. Routledge is an imprint of Taylor & Francis, an informa company.
Book Synopsis Artificial Intelligence and the Future of Testing by : Roy O. Freedle
Download or read book Artificial Intelligence and the Future of Testing written by Roy O. Freedle and published by Psychology Press. This book was released on 1990 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: First Published in 1990. Routledge is an imprint of Taylor & Francis, an informa company.
Written by a leading expert in the field, this unique volume contains current test design approaches and focuses only on software test design. Copeland illustrates each test design through detailed examples and step-by-step instructions.
Book Synopsis A Practitioner's Guide to Software Test Design by : Lee Copeland
Download or read book A Practitioner's Guide to Software Test Design written by Lee Copeland and published by Artech House. This book was released on 2004 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by a leading expert in the field, this unique volume contains current test design approaches and focuses only on software test design. Copeland illustrates each test design through detailed examples and step-by-step instructions.
The book "Accelerating Software Quality: Machine Learning and Artificial Intelligence in the Age of DevOps" is a complete asset for software developers, testers, and managers that are on their journey to a more mature DevOps workflow, and struggle with better automation and data-driven decision making. DevOps is a mature process across the entire market, however, with existing Non-AI/ML technologies and models, it comes short in expediting release cycle, identifying productivity gaps and addressing them. This book, that was implemented by myself with the help of leaders from the DevOps and test automation space, is covering topics from basic introduction to AI and ML in software development and testing, implications of AI and ML on existing apps, processes, and tools, practical tips in applying commercial and open-source AI/ML tools within existing tool chain, chat-bots testing, visual based testing using AI, automated security scanning for vulnerabilities, automated code reviews, API testing and management using AI/ML, reducing effort and time through test impact analysis (TIA), robotic process automation (RPA), AIOps for smarter code deployments and production defects prevention, and many more.When properly leveraging such tools, DevOps teams can benefit from greater code quality and functional and non-functional test automation coverage. This increases their release cycle velocity, reduces noise and software waste, and enhances their app quality.The book is divided into 3 main sections: *Section 1 covers the fundamentals of AI and ML in software development and testing. It includes introductions, definitions, 101 for testing AI-Based applications, classifications of AI/ML and defects that are tied to AI/ML, and more.*Section 2 focuses on practical advises and recommendations for using AI/ML based solutions within software development activities. This section includes topics like visual AI test automation, AI in test management, testing conversational AI applications, RPA benefits, API testing and much more.*Section 3 covers the more advanced and future-looking angles of AI and ML with projections and unique use cases. Among the topics in this section are AI and ML in logs observability, AIOps benefits to an entire DevOps teams, how to maintain AI/ML test automation, Test impact analysis with AI, and more.The book is packed with many proven best practices, real life examples, and many other open source and commercial solution recommendations that are set to shape the future of DevOps together with ML/AI
Book Synopsis Accelerating Software Quality by : Eran Kinsbruner
Download or read book Accelerating Software Quality written by Eran Kinsbruner and published by Independently Published. This book was released on 2020-08-10 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book "Accelerating Software Quality: Machine Learning and Artificial Intelligence in the Age of DevOps" is a complete asset for software developers, testers, and managers that are on their journey to a more mature DevOps workflow, and struggle with better automation and data-driven decision making. DevOps is a mature process across the entire market, however, with existing Non-AI/ML technologies and models, it comes short in expediting release cycle, identifying productivity gaps and addressing them. This book, that was implemented by myself with the help of leaders from the DevOps and test automation space, is covering topics from basic introduction to AI and ML in software development and testing, implications of AI and ML on existing apps, processes, and tools, practical tips in applying commercial and open-source AI/ML tools within existing tool chain, chat-bots testing, visual based testing using AI, automated security scanning for vulnerabilities, automated code reviews, API testing and management using AI/ML, reducing effort and time through test impact analysis (TIA), robotic process automation (RPA), AIOps for smarter code deployments and production defects prevention, and many more.When properly leveraging such tools, DevOps teams can benefit from greater code quality and functional and non-functional test automation coverage. This increases their release cycle velocity, reduces noise and software waste, and enhances their app quality.The book is divided into 3 main sections: *Section 1 covers the fundamentals of AI and ML in software development and testing. It includes introductions, definitions, 101 for testing AI-Based applications, classifications of AI/ML and defects that are tied to AI/ML, and more.*Section 2 focuses on practical advises and recommendations for using AI/ML based solutions within software development activities. This section includes topics like visual AI test automation, AI in test management, testing conversational AI applications, RPA benefits, API testing and much more.*Section 3 covers the more advanced and future-looking angles of AI and ML with projections and unique use cases. Among the topics in this section are AI and ML in logs observability, AIOps benefits to an entire DevOps teams, how to maintain AI/ML test automation, Test impact analysis with AI, and more.The book is packed with many proven best practices, real life examples, and many other open source and commercial solution recommendations that are set to shape the future of DevOps together with ML/AI
This book explores AI from that angle and is aimed at testing and quality management practitioners who want to understand more, starting with the relationship between AI and trustworthiness, the issue of bias, and the complexities of testing machine learning systems. --
Book Synopsis Artificial Intelligence and Software Testing by : Rex Black
Download or read book Artificial Intelligence and Software Testing written by Rex Black and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores AI from that angle and is aimed at testing and quality management practitioners who want to understand more, starting with the relationship between AI and trustworthiness, the issue of bias, and the complexities of testing machine learning systems. --
This book will teach you how to test computer software under real-world conditions. The authors have all been test managers and software development managers at well-known Silicon Valley software companies. Successful consumer software companies have learned how to produce high-quality products under tight time and budget constraints. The book explains the testing side of that success. Who this book is for: * Testers and Test Managers * Project Managers-Understand the timeline, depth of investigation, and quality of communication to hold testers accountable for. * Programmers-Gain insight into the sources of errors in your code, understand what tests your work will have to pass, and why testers do the things they do. * Students-Train for an entry-level position in software development. What you will learn: * How to find important bugs quickly * How to describe software errors clearly * How to create a testing plan with a minimum of paperwork * How to design and use a bug-tracking system * Where testing fits in the product development process * How to test products that will be translated into other languages * How to test for compatibility with devices, such as printers * What laws apply to software quality
Book Synopsis Testing Computer Software by : Cem Kaner
Download or read book Testing Computer Software written by Cem Kaner and published by John Wiley & Sons. This book was released on 1999-04-26 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will teach you how to test computer software under real-world conditions. The authors have all been test managers and software development managers at well-known Silicon Valley software companies. Successful consumer software companies have learned how to produce high-quality products under tight time and budget constraints. The book explains the testing side of that success. Who this book is for: * Testers and Test Managers * Project Managers-Understand the timeline, depth of investigation, and quality of communication to hold testers accountable for. * Programmers-Gain insight into the sources of errors in your code, understand what tests your work will have to pass, and why testers do the things they do. * Students-Train for an entry-level position in software development. What you will learn: * How to find important bugs quickly * How to describe software errors clearly * How to create a testing plan with a minimum of paperwork * How to design and use a bug-tracking system * Where testing fits in the product development process * How to test products that will be translated into other languages * How to test for compatibility with devices, such as printers * What laws apply to software quality
Software Testing presents one of the first comprehensive guides to testing activities, ranging from test planning through test completion for every phase of software under development, and software under revision. Real life case studies are provided to enhance understanding as well as a companion website with tools and examples.
Book Synopsis Software Testing by : Gerald D. Everett
Download or read book Software Testing written by Gerald D. Everett and published by John Wiley & Sons. This book was released on 2007-07-27 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software Testing presents one of the first comprehensive guides to testing activities, ranging from test planning through test completion for every phase of software under development, and software under revision. Real life case studies are provided to enhance understanding as well as a companion website with tools and examples.
