Ai Driven Software Testing
DOWNLOAD
Download Ai Driven Software Testing PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Ai Driven Software Testing book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Ai Driven Software Testing
DOWNLOAD
Author : Srinivasa Rao Bittla
language : en
Publisher: Springer Nature
Release Date : 2025-10-21
Ai Driven Software Testing written by Srinivasa Rao Bittla and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-21 with Computers categories.
AI-Driven Software Testing explores how Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing quality engineering (QE), making testing more intelligent, efficient, and adaptive. The book begins by examining the critical role of QE in modern software development and the paradigm shift introduced by AI/ML. It traces the evolution of software testing, from manual approaches to AI-powered automation, highlighting key innovations that enhance accuracy, speed, and scalability. Readers will gain a deep understanding of quality engineering in the age of AI, comparing traditional and AI-driven testing methodologies to uncover their advantages and challenges. Moving into practical applications, the book delves into AI-enhanced test planning, execution, and defect management. It explores AI-driven test case development, intelligent test environments, and real-time monitoring techniques that streamline the testing lifecycle. Additionally, it covers AI’s impact on continuous integration and delivery (CI/CD), predictive analytics for failure prevention, and strategies for scaling AI-driven testing across cloud platforms. Finally, it looks ahead to the future of AI in software testing, discussing emerging trends, ethical considerations, and the evolving role of QE professionals in an AI-first world. With real-world case studies and actionable insights, AI-Driven Software Testing is an essential guide for QE engineers, developers, and tech leaders looking to harness AI for smarter, faster, and more reliable software testing. What you will learn: • What are the key principles of AI/ML-driven quality engineering • What is intelligent test case generation and adaptive test automation • Explore predictive analytics for defect prevention and risk assessment • Understand integration of AI/ML tools in CI/CD pipelines Who this book is for: Quality Engineers looking to enhance software testing with AI-driven techniques. Data Scientists exploring AI applications in software quality assurance and engineering. Software Developers – Engineers seeking to integrate AI/ML into testing and automation workflows.
Focus On Qa
DOWNLOAD
Author : Sai Chand Boyapati
language : en
Publisher: Sai Chand Boyapati
Release Date :
Focus On Qa written by Sai Chand Boyapati and has been published by Sai Chand Boyapati this book supported file pdf, txt, epub, kindle and other format this book has been release on with Technology & Engineering categories.
This book provides a comprehensive guide to modern software testing through the lens of AI. Explore practical applications, ethical considerations, and functional and security testing strategies. Authored by an industry expert, this book shares real-world experiences in launching large-scale products with quality assurance at the forefront. Whether you are a QA professional, developer, or tech enthusiast, this book is valuable for mastering AI-driven software testing and security processes.
Ai Infused Test Automation Revolutionizing Software Testing Through Artificial Intelligence
DOWNLOAD
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.
Software Testing With Generative Ai
DOWNLOAD
Author : Mark Winteringham
language : en
Publisher: Simon and Schuster
Release Date : 2024-12-10
Software Testing With Generative Ai written by Mark Winteringham and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-10 with Computers categories.
"The more you test, the more you learn about your software. Software Testing with Generative AI shows you how you can expand, automate, and enhance your testing with Large Language Model (LLM)-based AI. Your team will soon be delivering higher quality tests, all in less time"--
Ai Driven Testing
DOWNLOAD
Author : Tariq King
language : en
Publisher:
Release Date : 2021
Ai Driven Testing written by Tariq King and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Software testing is expensive. Through up-front and recurring investment in labor and assets, organizations spend roughly half of their engineering budget on testing activities. The good news is that automated testing efforts have begun to improve through recent advances in AI and machine learning. With this report, you'll learn how AI-driven approaches are helping organizations overcome problems that traditional automated testing tools can't touch. Author Tariq King, chief scientist at test.ai, helps you examine several AI-driven solutions for software testing issues. You'll explore the application of AI and ML to functional, structural performance, and user design testing, and then dive into techniques for automating graphically intensive solutions such as video streaming and gaming applications. You'll learn the current benefits and limitations of AI-driven testing, available applications, and insights into the future of this new and emerging discipline. Learn the challenges and limitations of traditional approaches to software test automation Explore how AI is advancing the state of the art in automated functional, structural, performance, and user design testing in several application domains Examine the costs, benefits, and possible applications of AI-driven testing Look at ways that AI-driven test automation tools will evolve over the next decade.
Automating Specification Based Software Testing
DOWNLOAD
Author : Robert M. Poston
language : en
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Release Date : 1996
Automating Specification Based Software Testing written by Robert M. Poston and has been published by Institute of Electrical & Electronics Engineers(IEEE) this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.
Fundamentals; Test generation; Test execution; Test evaluation; Software testing tools; Appendixes.
Generative Ai For Software Development
DOWNLOAD
Author : Seifedine Kadry
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2025-06-30
Generative Ai For Software Development written by Seifedine Kadry and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Computers categories.
As the field of Artificial Intelligence continues to evolve, Generative AI has emerged as a powerful tool in the realm of software development. AI models capable of generating high-quality, human-like code can significantly accelerate the software development process, assist in troubleshooting, and even automate tasks traditionally performed by human developers. Generative AI models, such as OpenAI, DeepMind, and others, are already demonstrating the ability to write functional code, generate documentation, and assist in code review. These models are not only reducing the time it takes to develop applications but are also making software development more accessible to a broader audience, including non-technical users. This book is intended to serve as a comprehensive guide for developers, technology leaders, and anyone interested in understanding how to leverage Generative AI in software development. It will cover the underlying technology behind these models, practical use cases, integration into development workflows, and ethical considerations. Additionally, it explores how the democratization of coding through AI will shape the future of software engineering. By providing insights into real-world applications and best practices for integrating generative AI into the software lifecycle, this book empowers readers to stay ahead of the technological curve in a rapidly evolving industry.
Acm Transactions On Software Engineering And Methodology
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1997
Acm Transactions On Software Engineering And Methodology written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Electronic journals categories.
Intelligent Assurance Artificial Intelligence Powered Software Testing In The Modern Development Lifecycle
DOWNLOAD
Author : Partha Sarathi Mohapatra
language : en
Publisher: Deep Science Publishing
Release Date : 2025-07-27
Intelligent Assurance Artificial Intelligence Powered Software Testing In The Modern Development Lifecycle written by Partha Sarathi Mohapatra and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-27 with Computers categories.
Traditional testing can’t match the speed and reliability demanded in modern software development and releases. This book explains the integration of Artificial Intelligence is transforming software testing—enabling smarter, faster, and more scalable quality assurance across the development lifecycle. This book demystifies the integration of AI, machine learning, and natural language processing into modern testing workflows. From automated test case generation and defect prediction to adaptive test maintenance and intelligent prioritization, it offers practical insights and real-world applications that empower QA teams to deliver higher-quality software with greater efficiency. Through a structured, hands-on approach, readers will explore AI-driven testing strategies, tools, and architectures that align with DevOps and agile practices. The book also delves into ethical considerations, challenges in AI adoption, and the future of autonomous testing agents. Whether you're a software tester, QA lead, DevOps engineer, or technology decision-maker, this book equips you with the knowledge to embrace AI-driven testing as a strategic advantage in delivering resilient, secure, and high-performance software.
Ai Powered Software Quality Assurance Transforming Testing With Ai And Machine Learning
DOWNLOAD
Author : Amit Bhanushali
language : en
Publisher: Xoffencerpublication
Release Date : 2023-10-30
Ai Powered Software Quality Assurance Transforming Testing With Ai And Machine Learning written by Amit Bhanushali and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-30 with Computers categories.
New challenges have arisen for the construction of contemporary AI-based systems as a result of recent developments in artificial intelligence (AI), in particular machine learning (ML) and deep learning (DL), and their incorporation into software-based systems utilized in all sectors of the economy. These systems place a heavy reliance on data, are constantly evolving and bettering themselves, and display a degree of intrinsic nondeterminism. As a consequence, their behavior displays a degree of uncertainty that is universally acknowledged. As a result of these characteristics, the field of software engineering has to devise adaptable and innovative approaches to quality assurance (QA) that are capable of both constructive and in-depth analysis. This is essential in order to guarantee the product's high quality throughout the whole development process as well as while it is being put to use in actual settings. On the other hand, as Borg has pointed out, the concept of "quality" in AI-based systems does not yet have a definitive definition at this time. As was noted before, the terminology that is utilized in the field of artificial intelligence and software engineering is distinct from one another. When developing AI-based systems, the knowledge and experiences of a wide variety of organizations are combined and utilized in the construction process. While this does lead to new and creative ways, exciting breakthroughs, and a major advancement in what can be done with current AI-based systems, it also encourages the babel of language, concepts, perceptions, and underlying assumptions and principles. While this does lead to new and creative methods, exciting breakthroughs, and a substantial advancement in what can be done with current AI-based systems, this does lead to new and creative approaches. While this does result in novel and creative methods, exciting discoveries, and a significant leap forward in terms of what can be accomplished with contemporary AI-based systems, it does so in spite of the fact that. For instance, in the field of machine learning (ML), the term "regression" may be used to refer to regression models or regression analysis, but in the field of software engineering (SE), the term "regression" is used to refer to regression testing. However, in the context of machine learning (ML), the term "testing" refers to the evaluation of performance characteristics (such as accuracy) of a trained model using a holdout validation dataset. In the context of software engineering (SE), "testing" is described as the activity of executing the system in order to uncover errors. As a consequence of this, there is an increasing amount of confusion, as well as the potential of solutions that are in contradiction with one another, about how to approach quality assurance for AI-based systems and how to deal with the challenges that are associated with it. This is because of the fact that there are a growing number of solutions that are based on AI. Although the authors of this study begin their investigation from the perspective of software engineering, their ultimate goal is to include and talk about a wide variety of different points of view, all of which will eventually come together to provide a multi-dimensional picture of quality assurance for AI-based systems. While the authors of this study begin their investigation from the perspective of software engineering, their ultimate goal is to include and talk about a wide variety of different points of view. In the first part of this study project, our primary focus is on defining the terminologies related with artificial intelligence quality assurance. In the following section, Section 3, we will discuss the challenges that are involved with QA for AI. In the last part of the inquiry, we will summarize what we found and form our conclusions.