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Artificial Intelligence Methods For Optimization Of The Software Testing Process


Artificial Intelligence Methods For Optimization Of The Software Testing Process
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Artificial Intelligence Methods For Optimization Of The Software Testing Process


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



Intelligent Assurance Artificial Intelligence Powered Software Testing In The Modern Development Lifecycle


Intelligent Assurance Artificial Intelligence Powered Software Testing In The Modern Development Lifecycle
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Author : Partha 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 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.



Artificial Intelligence Methods For Software Engineering


Artificial Intelligence Methods For Software Engineering
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Author : Meir Kalech
language : en
Publisher: World Scientific
Release Date : 2021-06-15

Artificial Intelligence Methods For Software Engineering written by Meir Kalech and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-15 with Computers categories.


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)



Handbook Of Research On Manufacturing Process Modeling And Optimization Strategies


Handbook Of Research On Manufacturing Process Modeling And Optimization Strategies
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Author : Das, Raja
language : en
Publisher: IGI Global
Release Date : 2017-03-10

Handbook Of Research On Manufacturing Process Modeling And Optimization Strategies written by Das, Raja and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-10 with Business & Economics categories.


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.



Advanced Topics In Inverse Data Envelopment Analysis


Advanced Topics In Inverse Data Envelopment Analysis
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Author : Mehdi Soltanifar
language : en
Publisher: Academic Press
Release Date : 2025-07-11

Advanced Topics In Inverse Data Envelopment Analysis written by Mehdi Soltanifar and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-11 with Computers categories.


Advanced Topics in Inverse Data Envelopment Analysis: Approaches for Handling Ratio Data explores and tackles the most significant challenges encountered by researchers and practitioners in decision analysis and performance evaluation. This book delves into the sophisticated realm of Ratio Data Envelopment Analysis (DEA-R), offering a thorough examination of advanced methodologies, practical examples, and insights into managing complex problems involving both non-negative and negative data. Filling crucial gaps in existing literature, this comprehensive resource focuses on the emerging field of Inverse DEA-R, equipping readers with the necessary tools and knowledge to address a wide range of challenging data types. This book serves as an essential guide for making informed and efficient decisions, guiding researchers and graduate students in computer science, applied mathematics, industrial engineering, and finance, navigating the complexities of decision analysis in today's data-driven world. - Offers an in-depth exploration of Inverse DEA-R models, making it an invaluable resource for researchers seeking to understand and apply these advanced techniques - Includes numerous practical examples and case studies across different industries demonstrating how Inverse DEA-R can be applied to real-world scenarios - Highlights potential areas for further research and development within Inverse DEA-R, encouraging readers to explore new avenues and contribute to the advancement of the field



Decision Making Models


Decision Making Models
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Author : Tofigh Allahviranloo
language : en
Publisher: Elsevier
Release Date : 2024-07-24

Decision Making Models written by Tofigh Allahviranloo and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-24 with Computers categories.


Decision Making Models: A Perspective of Fuzzy Logic and Machine Learning presents the latest developments in the field of uncertain mathematics and decision science. The book aims to deliver a systematic exposure to soft computing techniques in fuzzy mathematics as well as artificial intelligence in the context of real-life problems and is designed to address recent techniques to solving uncertain problems encountered specifically in decision sciences. Researchers, professors, software engineers, and graduate students working in the fields of applied mathematics, software engineering, and artificial intelligence will find this book useful to acquire a solid foundation in fuzzy logic and fuzzy systems, optimization problems and artificial intelligence practices, as well as how to analyze IoT solutions with applications and develop decision making mechanisms realized under uncertainty. - Introduces mathematics of intelligent systems which provides the usage of mathematical rigor such as precise definitions, theorems, results, and proofs - Provides extended and new comprehensive methods which can be used efficiently in a fuzzy environment as well as optimization problems and related fields - Covers applications and elaborates on the usage of the developed methodology in various fields of industry such as software technologies, biomedicine, image processing, and communications



Artificial Intelligence Methods In Software Testing


Artificial Intelligence Methods In Software Testing
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Author : Mark Last
language : en
Publisher: World Scientific
Release Date : 2004-06-03

Artificial Intelligence Methods In Software Testing written by Mark Last and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-06-03 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.



Reachable Sets Of Dynamic Systems


Reachable Sets Of Dynamic Systems
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Author : Stanislaw Raczynski
language : en
Publisher: Elsevier
Release Date : 2023-04-21

Reachable Sets Of Dynamic Systems written by Stanislaw Raczynski and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-21 with Computers categories.


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



Handbook Of Metaheuristic Algorithms


Handbook Of Metaheuristic Algorithms
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Author : Chun-Wei Tsai
language : en
Publisher: Elsevier
Release Date : 2023-05-30

Handbook Of Metaheuristic Algorithms written by Chun-Wei Tsai and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-30 with Computers categories.


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



Models And Methods For Systems Engineering


Models And Methods For Systems Engineering
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Author : Grzegorz Borowik
language : en
Publisher: Springer Nature
Release Date : 2025-04-19

Models And Methods For Systems Engineering written by Grzegorz Borowik and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-19 with Computers categories.


This book compiles high-quality research contributions from leading experts, providing both theoretical foundations and practical methodologies that are shaping the future of engineering systems. In an era where technological innovation drives every industry, this book offers a comprehensive exploration of cutting-edge approaches in systems optimization, artificial intelligence, and digital transformation. Divided into three distinct sections—Advanced Technologies in Control, Optimization, and Communication Systems; Artificial Intelligence, Machine Learning, and Cybersecurity; and Human-Computer Interaction, Digital Transformation, and Future Internet Technologies—this book covers a wide range of topics essential for today’s engineers and researchers. From the latest advancements in spacecraft orbit control and energy-efficient IoT data management to groundbreaking work in medical diagnostics using AI, the book delivers a diverse array of applications across industries. This book is an invaluable resource for scientists, engineers, IT specialists, and students seeking to understand the complexities and opportunities in modern systems engineering. Whether you are a researcher looking for state-of-the-art techniques or a professional seeking practical solutions for engineering challenges, this book is designed to equip you with the tools and knowledge to succeed in a rapidly evolving field. Discover how the latest models and methods in systems engineering are reshaping technology and driving innovation across industries. This essential guide is perfect for professionals in fields such as computational intelligence, control engineering, artificial intelligence, signal processing, and digital transformation. It also serves as a robust reference for academic researchers, and students involved in engineering and applied science disciplines.