Overview

The rapid evolution of software engineering demands innovative approaches to meet the growing complexity and scale of modern software systems. Traditional methods often need help to keep pace with the demands for efficiency, reliability, and scalability. Manual development, testing, and maintenance processes are time-consuming and error-prone, leading to delays and increased costs. Additionally, integrating new technologies, such as AI, ML, Federated Learning, and Large Language Models (LLM), presents unique challenges in terms of implementation and ethical considerations. Advancing Software Engineering Through AI, Federated Learning, and Large Language Models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. It equips readers with the knowledge and practical insights needed to harness these technologies effectively, enhancing software development, testing, maintenance, and deployment processes. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Researchers, academicians, practitioners, industrialists, and students will benefit from the interdisciplinary insights provided by experts in AI, ML, software engineering, and ethics. Moreover, the forward-looking section discussing future trends and research directions will inspire readers to explore new avenues in software engineering. This book serves as a valuable resource for those seeking to leverage advanced technologies to improve software engineering processes, making it an essential addition to the library of anyone involved in software development.

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Dr. Avinash Kumar Sharma currently working as Associate Professor, Department of Computer Science & Engineering, Sharda School of Engineering & Technology (SSET), Sharda University., Greater Noida. My research areas are Cloud Computing, Machine Learning, Smart Agriculture, Artificial Intelligence. I have 17 years of teaching experience. I have published about 25 research papers in national / international conferences, journals and book chapters. I have published 03 patents including 01 design patents. Nitin Chanderwal is currently working as an Associate Professor Educator-Full Time in the Department of Electrical and Computer Engineering at University of Cincinnati. In the past I have worked as Associate Professor-Full Time of Information Systems and Analytics at IIM Shillong, Meghalaya, INDIA. During his tenure at IIM Shillong he also served as Chairperson for the Areas: {(Information Systems and Analytics) & (IT Services and Website Committee)}. During 2017-2018, He has worked as Professor Educator in the Department of EECS at University of Cincinnati, OH and during 2010-2011 as First Tier Bank Professor in the Peter Kiewit Institute at University of Nebraska at Omaha, NE, USA. In July 2001, he received B.Engg. in Computer Science & Engineering [Hons.] from Dr. B.R. Ambedkar University, Agra and M.Engg. in Software Engineering from Thapar University, erstwhile Thapar Institute of Engineering and Technology (Deemed University), Patiala, Punjab, INDIA in March 2003. In September 2008, he received Ph.D. in Computer Science & Engineering from Jaypee University of Information Technology, INDIA and University of Florida (UF), Gainesville, FL, USA under student exchange program, specifically he has completed 12 credits course work from UF. In May 2013, he received D.Sc. in Computer Science & Engineering from Uttarakhand Technical University, Dehradun, INDIA. I completed partial research work of D.Sc. at University of Nebraska at Omaha (UNO), NE, USA. He is a IBM certified engineer, a Life Member of IAENG, Senior Member of IEEE, ACM & IACSIT and Member of SIAM and ACIS and have published 200+ Research Papers in peer reviewed International Journals & Transactions, Book Chapters, Symposium, Conferences and Position. He has bagged more than 50 academic and research awards. My research interest includes Blockchain Technology, Cyber Physical Systems, Big Data Analytics, Social Networks especially Computer Mediated Communications & Flaming, Interconnection Networks & Architecture, Fault-tolerance & Reliability, NoCs, SoCs, and NiPs, Application of Stable Matching Problems, Stochastic Communication and Sensor Networks. He has received 2 Indian Patents and 1 Australian Patent during 2020-2021. he is also an Associate Editor of the International Journal of Parallel, Emergent and Distributed Systems, Taylor and Francis, UK and IEEE Access, IEEE, USA. Pancham Singh currently working as an Assistant Professor in the Department of Information Technology, AKGEC, Ghaziabad Since 2007 to till date. He has more than 16+ years of teaching experience and 1.5 years of industry experience. He received B.Tech. degree in Computer Science & Engineering from Dr. A.P.J. Abdul Kalam Technical University, [formely known as a UPTU], Lucknow in 2005, Master's degree in Information Technology from RTU, Kota, Rajasthan in 2014 and Pursuing PhD from Netaji Subhas University of Technology (NSUT), Delhi since Jan' 2023. He has authored two books Operating Systems and Graph Theory. He has presented and published more than 10 papers in International Journals/ Conferences. He had reviewed papers for the International Conferences ICDT and ICISML 2023. He has published 6 National and International Patents. His area of interest are AI&ML, WSN, SE, Blockchain, IoT and Social Networking. Mrignainy Kansal is currently pursuing her PhD in Computer Science and Engineering from Netaji Subhas University of Technology (NSUT), New Delhi. Alongside her studies, she holds the position of an Assistant Professor at Ajay Kumar Garg Engineering College, Ghaziabad. She completed her BTech Degree in Information Technology from AKTU and further pursued her MTech in Information Technology from Guru Gobind Singh Indraprastha University, Delhi. She has a good record of publications at various International Conferences. Additionally, she has qualified GATE-2016 and GATE-2023. Her expertise lies in diverse areas such as Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, and Software Engineering.

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