Optimising The Software Development Process With Artificial Intelligence

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.

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

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. ·

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)

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.

"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.

This book provides a structured overview of artificial intelligence-empowered applied software engineering. Evolving technological advancements in big data, smartphone and mobile software applications, the Internet of Things and a vast range of application areas in all sorts of human activities and professions lead current research towards the efficient incorporation of artificial intelligence enhancements into software and the empowerment of software with artificial intelligence. This book at hand, devoted to Novel Methodologies to Engineering Smart Software Systems Novel Methodologies to Engineering Smart Software Systems, constitutes the first volume of a two-volume Handbook on Artificial Intelligence-empowered Applied Software Engineering. Topics include very significant advances in (i) Artificial Intelligence-Assisted Software Development and (ii) Software Engineering Tools to develop Artificial Intelligence Applications, as well as a detailed Survey of Recent Relevant Literature. Professors, researchers, scientists, engineers and students in artificial intelligence, software engineering and computer science-related disciplines are expected to benefit from it, along with interested readers from other disciplines.

Code Convergence: Navigating the New Era of AI in Software Engineering The rapid advancement of artificial intelligence in generating code poses both challenges and opportunities for software engineers. Code Convergence dives deep into the implications of this technological evolution, offering readers a comprehensive guide to staying relevant and harnessing AI's power in software development. This illuminating read is meticulously designed for everyone from budding engineers to seasoned software wizards, exploring the profound changes and strategies needed in the age of automation. Embark on a journey through thoughtfully crafted chapters that unravel the complexities of AI's role in software engineering. Discover practical strategies for leveraging AI tools, learn how to enhance your software design with AI's capabilities, and understand the evolving role of software engineers augmented by machine intelligence. With a blend of theoretical insights and real-world applications, Code Convergence empowers engineers to adapt and thrive in this transformative landscape. From comprehending how AI-generated code is changing the software development lifecycle, to exploring methods for integrating AI seamlessly into your projects, this book covers the spectrum of necessity and innovation. Uncover the secrets of staying ahead in your career by embracing and enhancing AI technologies, ensuring your expertise remains indispensable in the future of engineering. The realm of software engineering is at a pivotal turning point, and Code Convergence serves as your guide. Prepare to explore, understand, and revolutionize your approach to software development with AI as your ally. The future beckons, and it's filled with endless possibilities for those ready to embrace the change. Table of Contents 1. The AI Revolution in Software Development - The Rise of AI-Generated Code - Strategies for Working Alongside AI - Implications for the Software Development Lifecycle 2. Staying Ahead in the Age of Automation - Adapting to the New Normal - Leveraging AI for Career Growth - Maintaining Relevance Amid Rapid Change 3. Enhancing Software Design with AI - Integrating AI into Development Processes - The Impact of AI on Creativity - Optimizing Performance with AI Tools 4. The Evolving Role of Software Engineers - From Coding to Complex Problem-Solving - Augmenting Skills with AI - The Future of Engineering Work 5. Practical Strategies for Leveraging AI - AI Tools Every Engineer Should Know - Implementing AI in Your Projects - Case Studies and Success Stories 6. Understanding AI's Impact on Code Quality - Comparative Analysis of Human vs. AI Code - Improving Code Efficiency with AI - Future Trends in Code Generation 7. Ethical Considerations in AI Development - Evaluating Bias in AI-Generated Code - Privacy and Security Challenges - Responsibility and Accountability of Engineers 8. Collaboration and Innovation with AI - Building AI-Enhanced Software Teams - Interdisciplinary Approaches to Development - Fostering a Culture of Continuous Learning 9. The Global Landscape of AI and Software Engineering - International Trends in AI Adoption - Cultural Influences on AI Development - Global Opportunities for Engineers 10. Navigating Career Pathways in AI-Era Engineering - Skills for the Future - Building a Portfolio of AI-Enhanced Projects - Networking and Community Engagement 11. AI and the Future of Software Design - Evolution of Design Paradigms - AI as a Design Partner - Redefining Creativity in Engineering 12. Conclusion: Embracing the Shift - Summarizing the Journey - Preparing for What Comes Next - The Endless Possibilities of AI in Engineering