Ai Infused Test Automation Revolutionizing Software Testing Through Artificial Intelligence
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Ai Infused Test Automation Revolutionizing Software Testing Through Artificial Intelligence
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Author : Anup Sahoo
language : en
Publisher: OrangeBooks Publication
Release Date : 2023-11-27
Ai Infused Test Automation Revolutionizing Software Testing Through Artificial Intelligence written by Anup Sahoo and has been published by OrangeBooks Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-27 with Juvenile Nonfiction categories.
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.
Accelerating Software Quality
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Author : Eran Kinsbruner
language : en
Publisher: Independently Published
Release Date : 2020-08-10
Accelerating Software Quality written by Eran Kinsbruner and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-10 with categories.
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
Artificial Intelligence Methods In Software Testing
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Author : Horst Bunke
language : en
Publisher: World Scientific
Release Date : 2004
Artificial Intelligence Methods In Software Testing written by Horst Bunke and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.
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."
Testing In The Digital Age
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Author : Tom van de Ven
language : en
Publisher: Uitgeverij kleine Uil
Release Date : 2018-06-02
Testing In The Digital Age written by Tom van de Ven and has been published by Uitgeverij kleine Uil this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-02 with Computers categories.
Testing in the digital age brings a new vision on test engineering, using new quality attributes that tackle intelligent machines and a roadmap split up in fi ve hops. With everything digital there are more possibilities for test automation and piles of (test) data growing out of control. Working together with robots (cobotics), using artifi cial intelligence in testing and eventually predict the occurrence of defects brings your testing to the digital age. We have interviewed companies on their view of digital testing. A glossary brings an extensive list of terms that supports you in all your test communications.
Optimization Of Automated Software Testing Using Meta Heuristic Techniques
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Author : Manju Khari
language : en
Publisher: Springer Nature
Release Date : 2022-09-26
Optimization Of Automated Software Testing Using Meta Heuristic Techniques written by Manju Khari and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-26 with Technology & Engineering categories.
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. ·
Application Of Artificial Intelligence To Assessment
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Author : Hong Jiao
language : en
Publisher: IAP
Release Date : 2020-03-01
Application Of Artificial Intelligence To Assessment written by Hong Jiao and has been published by IAP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-01 with Computers categories.
The general theme of this book is to present the applications of artificial intelligence (AI) in test development. In particular, this book includes research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing. By utilizing artificial intelligence, the efficiency of item development, test form construction, test delivery, and scoring could be dramatically increased. Chapters on automated item generation offer different perspectives related to generating a large number of items with controlled psychometric properties including the latest development of using machine learning methods. Automated scoring is illustrated for different types of assessments such as speaking and writing from both methodological aspects and practical considerations. Further, automated test assembly is elaborated for the conventional linear tests from both classical test theory and item response theory perspectives. Item pool design and assembly for the linear-on-the-fly tests elaborates more complications in practice when test security is a big concern. Finally, several chapters focus on computerized adaptive testing (CAT) at either item or module levels. CAT is further illustrated as an effective approach to increasing test-takers’ engagement in testing. In summary, the book includes both theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to automate the process of test development. While some of these automation processes have become common practices such as automated test assembly, automated scoring, and computerized adaptive testing, some others such as automated item generation calls for more research and exploration. When new AI methods are emerging and evolving, it is expected that researchers can expand and improve the methods for automating different steps in test development to enhance the automation features and practitioners can adopt quality automation procedures to improve assessment practices.
Artificial Intelligence Methods For Optimization Of The Software Testing Process
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Author : Sahar Tahvili
language : en
Publisher: Academic Press
Release Date : 2022-07-21
Artificial Intelligence Methods For Optimization Of The Software Testing Process written by Sahar Tahvili and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-21 with Computers categories.
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
Artificial Intelligence And Software Testing
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Author : Rex Black
language : en
Publisher:
Release Date : 2022
Artificial Intelligence And Software Testing written by Rex Black and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Artificial intelligence categories.
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. --
Automated Software Testing
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Author : Ajay Kumar Jena
language : en
Publisher: Springer Nature
Release Date : 2020-02-03
Automated Software Testing written by Ajay Kumar Jena and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-03 with Technology & Engineering categories.
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.
2019 Ieee International Conference On Artificial Intelligence Testing Aitest
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Author : IEEE Staff
language : en
Publisher:
Release Date : 2019-04-04
2019 Ieee International Conference On Artificial Intelligence Testing Aitest written by IEEE Staff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-04 with categories.
Topics of interest include (but are not limited to) the following A Testing AI applications, include (1) Methodologies for testing, verification and validation of AI applications, (2) Techniques for testing AI applications, (3) Tools and environment for automated and semi automated software testing AI applications for various testing activities and management of testing resources, (4) Specific concerns of software testing with various specific types of AI technologies, such as machine learning and data mining, genetic algorithms, multi agent systems, automatic reasoning and theorem proving, etc (5) Specific concerns of software testing for various types of AI applications B Applications of AI techniques to software testing, include (1) Machine learning applications to software testing, such as test case generation, test effectiveness prediction and optimization, test adequacy improvement, test cost reduction, etc C Data quality checking for AI applications