Ai Infused Test Automation Revolutionizing Software Testing Through Artificial Intelligence
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AI-Infused Test Automation: Revolutionizing Software Testing through Artificial Intelligence by Anup Sahoo Pdf
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 by Eran Kinsbruner Pdf
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 by Horst Bunke,Mark Last,Abraham Kandel Pdf
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."
Optimization of Automated Software Testing Using Meta-Heuristic Techniques by Manju Khari,Deepti Bala Mishra,Biswaranjan Acharya,Ruben Gonzalez Crespo Pdf
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 by Hong Jiao,Robert W. Lissitz Pdf
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.
Testing in the digital age by Tom van de Ven,Rik Marselis,Humayun Shaukat Pdf
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.
Artificial Intelligence Methods for Optimization of the Software Testing Process by Sahar Tahvili,Leo Hatvani Pdf
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
Automated Software Testing by Ajay Kumar Jena,Himansu Das,Durga Prasad Mohapatra Pdf
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.
Artificial Intelligence and Software Testing by Rex Black,James Davenport,Joanna Olszewska,Jeremias Robler,Adam Leon Smith,Jonathon Wright Pdf
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. --
A Simple Guide to Software Testing! by Narasimhan G R Pdf
Welcome to the world of software testing, where the effectiveness and reliability of software applications are put to the ultimate test. In this book, "Manual and Automated Software Testing," we embark on a journey to explore the intricate realm of software testing, shedding light on both manual and automated techniques that play a vital role in ensuring software quality in brief and simple way. In today's digital age, where software applications have become an integral part of our daily lives, it is essential to deliver products that not only meet user expectations but also function flawlessly. Software testing serves as the cornerstone of this process, enabling organizations to identify defects, mitigate risks, and provide a seamless user experience. You can learn the fundamentals & types of Software Testing, the key concepts, methodologies, and terminologies that form the basis of this discipline. From test planning and test case design to test execution and defect management, we cover the entire testing life cycle, providing you with a solid foundation. We delve into the world of manual testing, where human intervention plays a crucial role. We explore various techniques such as black-box testing, white-box testing, and grey-box testing, explaining their purpose and how they are executed. Through practical examples and real-world scenarios, we demonstrate how manual testing can effectively uncover defects and validate software functionality. Software Quality Automation has revolutionized the field of software testing, enabling faster and more efficient validation of applications. In this chapter, we demystify test automation, shedding light on the tools, frameworks, and best practices involved. Combining Manual and Automated Testing for Optimal Results While manual and automated testing techniques each have their strengths, combining them strategically can yield remarkable results. We also explore how manual and automated testing can complement each other, creating a robust testing approach. Effective test management and documentation are critical to any successful testing endeavor. We explore test management tools and methodologies that help streamline the testing process and ensure clear communication between testers, developers, and stakeholders. Special Testing area, software applications must also meet performance and security standards. The performance testing and security testing, two specialized areas within software testing. We discuss testing methods to evaluate application performance under different conditions and methods to identify vulnerabilities and protect against potential threats. We can also explore emerging trends such as artificial intelligence, machine learning, and DevOps, and their impact on the testing landscape. We also discuss the importance of continuous testing in an agile development environment. More advanced topics could be found from various online resources. Wish you good luck!
Advanced Automated Software Testing: Frameworks for Refined Practice by Alsmadi, Izzat Pdf
"This book discusses the current state of test automation practices, as it includes chapters related to software test automation and its validity and applicability in different domains"--Provided by publisher.
Test Automation Fundamentals by Manfred Baumgartner,Thomas Steirer,Marc-Florian Wendland,Stefan Gwihs,Julian Hartner,Richard Seidl Pdf
Test automation is an essential tool in today’s software development environments. It increases testing efficiency and makes test procedures reliably repeatable.
This book provides a complete overview of how to design test automation processes and integrate them into your organization or existing projects. It details functional and technical strategies and goes into detail on the relevant concepts and best practices. The book’s main focus is on functional system testing.
Topics covered:
• An introduction to test automation
• Objectives and success factors
• Preparing for test automation
• Introduction to generic test automation architectures
• Design and development of a test automation solution
• Risks and contingencies during deployment
• Metrics and reporting
• Transitioning manual testing to an automated environment
• Verifying a test automation solution
• Continuous improvement
The appendix contains an overview of software quality characteristics according to the ISO 25010 standard, and lists potential test automation applications within this context. It also provides an introduction to load and performance testing, and a sample catalog of criteria for selecting test automation tools.
This book is fully compliant with the ISTQB® syllabus and, with its many explanatory examples, is equally suitable for preparation for certification, as a concise reference book for anyone who wants to acquire this essential skill, or for university-level study.
2019 IEEE International Conference on Artificial Intelligence Testing (AITest) by IEEE Staff Pdf
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
The Future of Software Quality Assurance by Stephan Goericke Pdf
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. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
