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
Download or read book Optimization of Automated Software Testing Using Meta Heuristic Techniques written by Manju Khari and published by Springer Nature. This book was released on 2022-09-26 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides awareness of different evolutionary methods used for automatic generation and optimization of test data in the field of software testing. While the book highlights on the foundations of software testing techniques, it also focuses on contemporary topics for research and development. This book covers the automated process of testing in different levels like unit level, integration level, performance level, evaluation of testing strategies, testing in security level, optimizing test cases using various algorithms, and controlling and monitoring the testing process etc. This book aids young researchers in the field of optimization of automated software testing, provides academics with knowledge on the emerging field of AI in software development, and supports universities, research centers, and industries in new projects using AI in software testing. Supports the advancement in the artificial intelligence used in software development; Advances knowledge on artificial intelligence based metaheuristic approach in software testing; Encourages innovation in traditional software testing field using recent artificial intelligence. ·
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."
Download or read book Optimising the Software Development Process with Artificial Intelligence written by José Raúl Romero and published by Springer Nature. This book was released on 2023-07-19 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a practical introduction to the use of artificial intelligence (AI) techniques to improve and optimise the various phases of the software development process, from the initial project planning to the latest deployment. All chapters were written by leading experts in the field and include practical and reproducible examples. Following the introductory chapter, Chapters 2-9 respectively apply AI techniques to the classic phases of the software development process: project management, requirement engineering, analysis and design, coding, cloud deployment, unit and system testing, and maintenance. Subsequently, Chapters 10 and 11 provide foundational tutorials on the AI techniques used in the preceding chapters: metaheuristics and machine learning. Given its scope and focus, the book represents a valuable resource for researchers, practitioners and students with a basic grasp of software engineering.
Download or read book AI Infused Test Automation Revolutionizing Software Testing through Artificial Intelligence written by Anup Sahoo and published by OrangeBooks Publication. This book was released on 2023-11-27 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI-Infused Test Automation: Revolutionizing Software Testing through Artificial Intelligence is an enlightening book that explores the transformative power of AI in software testing. It covers a wide range of AI-driven techniques, tools, and practices, providing readers with a comprehensive understanding of how AI has revolutionized the field. The book inspires readers to embrace AI and leverage its capabilities to enhance test case generation, bug detection, performance testing, and test management. With AI, readers can achieve higher productivity, improved software quality, and enhanced customer satisfaction. This book catalyzes readers to embark on their AI-infused testing journey, driving innovation and shaping the future of software testing.
Download or read book Artificial Intelligence Applications for Improved Software Engineering Development New Prospects written by Meziane, Farid and published by IGI Global. This book was released on 2009-07-31 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides an overview of useful techniques in artificial intelligence for future software development along with critical assessment for further advancement"--Provided by publisher.
Download or read book Handbook of Research on Manufacturing Process Modeling and Optimization Strategies written by Das, Raja and published by IGI Global. This book was released on 2017-03-10 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent improvements in business process strategies have allowed more opportunities to attain greater developmental performances. This has led to higher success in day-to-day production and overall competitive advantage. The Handbook of Research on Manufacturing Process Modeling and Optimization Strategies is a pivotal reference source for the latest research on the various manufacturing methodologies and highlights the best optimization approaches to achieve boosted process performance. Featuring extensive coverage on relevant areas such as genetic algorithms, fuzzy set theory, and soft computing techniques, this publication is an ideal resource for researchers, practitioners, academicians, designers, manufacturing engineers, and institutions involved in design and manufacturing projects.
Download or read book Automated Software Testing written by Ajay Kumar Jena and published by Springer Nature. This book was released on 2020-02-03 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers both theory and applications in the automation of software testing tools and techniques for various types of software (e.g. object-oriented, aspect-oriented, and web-based software). When software fails, it is most often due to lack of proper and thorough testing, an aspect that is even more acute for object-oriented, aspect-oriented, and web-based software. Further, since it is more difficult to test distributed and service-oriented architecture-based applications, there is a pressing need to discuss the latest developments in automated software testing. This book discusses the most relevant issues, models, tools, challenges, and applications in automated software testing. Further, it brings together academic researchers, scientists, and engineers from a wide range of industrial application areas, who present their latest findings and identify future challenges in this fledging research area.
Download or read book Artificial Intelligence Methods In Software Testing written by Mark Last and published by World Scientific. This book was released on 2004-06-03 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.
Download or read book Artificial Intelligence and Software Engineering written by Derek Partridge and published by Routledge. This book was released on 2013-04-11 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Managers, business owners, computer literate individuals, software developers, students, and researchers--all are looking for an understanding of artificial intelligence (AI) and what might be in the future. In this literate yet easy-to-read discussion, Derek Partridge explains what artificial intelligence can and cannot do, and what it holds for applications such as banking, financial services, and expert systems of all kinds. Topics include: the strengths and weaknesses of software development and engineering; machine learning and its promises and problems; expert systems and success stories; and practical software through artificial intelligence.
Download or read book Handbook of Metaheuristic Algorithms written by Chun-Wei Tsai and published by Elsevier. This book was released on 2023-05-30 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Metaheuristic Algorithms: From Fundamental Theories to Advanced Applications provides a brief introduction to metaheuristic algorithms from the ground up, including basic ideas and advanced solutions. Although readers may be able to find source code for some metaheuristic algorithms on the Internet, the coding styles and explanations are generally quite different, and thus requiring expanded knowledge between theory and implementation. This book can also help students and researchers construct an integrated perspective of metaheuristic and unsupervised algorithms for artificial intelligence research in computer science and applied engineering domains. Metaheuristic algorithms can be considered the epitome of unsupervised learning algorithms for the optimization of engineering and artificial intelligence problems, including simulated annealing (SA), tabu search (TS), genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), differential evolution (DE), and others. Distinct from most supervised learning algorithms that need labeled data to learn and construct determination models, metaheuristic algorithms inherit characteristics of unsupervised learning algorithms used for solving complex engineering optimization problems without labeled data, just like self-learning, to find solutions to complex problems. Presents a unified framework for metaheuristics and describes well-known algorithms and their variants Introduces fundamentals and advanced topics for solving engineering optimization problems, e.g., scheduling problems, sensors deployment problems, and clustering problems Includes source code based on the unified framework for metaheuristics used as examples to show how TS, SA, GA, ACO, PSO, DE, parallel metaheuristic algorithm, hybrid metaheuristic, local search, and other advanced technologies are realized in programming languages such as C++ and Python
Download or read book Reachable Sets of Dynamic Systems written by Stanislaw Raczynski and published by Elsevier. This book was released on 2023-04-21 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reachable Sets of Dynamic Systems: Uncertainty, Sensitivity, and Complex Dynamics introduces differential inclusions, providing an overview as well as multiple examples of its interdisciplinary applications. The design of dynamic systems of any type is an important issue as is the influence of uncertainty in model parameters and model sensitivity. The possibility of calculating the reachable sets may be a powerful additional tool in such tasks. This book can help graduate students, researchers, and engineers working in the field of computer simulation and model building, in the calculation of reachable sets of dynamic models. Introduces methodologies and approaches to the modeling and simulation of dynamic systems Presents uncertainty treatment and model sensitivity are described, and interdisciplinary examples Explores applications of differential inclusions in modeling and simulation
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)
Download or read book Applications of Artificial Intelligence in Process Systems Engineering written by Jingzheng Ren and published by Elsevier. This book was released on 2021-06-05 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis Gives direction to future development trends of AI technologies in chemical and process engineering
Download or read book Computational Intelligence In Software Quality Assurance written by Scott Dick and published by World Scientific. This book was released on 2005-10-19 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Artificial Intelligence Methods for Software Engineering written by Meir Kalech and published by World Scientific Publishing Company. This book was released on 2021 with total page 0 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)
Download or read book Analytic Methods in Systems and Software Testing written by Ron S. Kenett and published by John Wiley & Sons. This book was released on 2018-09-04 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive treatment of systems and software testing using state of the art methods and tools This book provides valuable insights into state of the art software testing methods and explains, with examples, the statistical and analytic methods used in this field. Numerous examples are used to provide understanding in applying these methods to real-world problems. Leading authorities in applied statistics, computer science, and software engineering present state-of-the-art methods addressing challenges faced by practitioners and researchers involved in system and software testing. Methods include: machine learning, Bayesian methods, graphical models, experimental design, generalized regression, and reliability modeling. Analytic Methods in Systems and Software Testing presents its comprehensive collection of methods in four parts: Part I: Testing Concepts and Methods; Part II: Statistical Models; Part III: Testing Infrastructures; and Part IV: Testing Applications. It seeks to maintain a focus on analytic methods, while at the same time offering a contextual landscape of modern engineering, in order to introduce related statistical and probabilistic models used in this domain. This makes the book an incredibly useful tool, offering interesting insights on challenges in the field for researchers and practitioners alike. Compiles cutting-edge methods and examples of analytical approaches to systems and software testing from leading authorities in applied statistics, computer science, and software engineering Combines methods and examples focused on the analytic aspects of systems and software testing Covers logistic regression, machine learning, Bayesian methods, graphical models, experimental design, generalized regression, and reliability models Written by leading researchers and practitioners in the field, from diverse backgrounds including research, business, government, and consulting Stimulates research at the theoretical and practical level Analytic Methods in Systems and Software Testing is an excellent advanced reference directed toward industrial and academic readers whose work in systems and software development approaches or surpasses existing frontiers of testing and validation procedures. It will also be valuable to post-graduate students in computer science and mathematics.
