Generative AI for Web Engineering Models

Generative AI for Web Engineering Models

Projected Release Date: September, 2024|Copyright: © 2024 |Pages: 320
DOI: 10.4018/979-8-3693-3703-5
ISBN13: 9798369337035|EISBN13: 9798369337042
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Description & Coverage
Description:

Web engineering faces a pressing challenge in keeping pace with the rapidly evolving digital landscape. Developing, designing, testing, and maintaining web-based systems and applications require innovative approaches to meet the growing demands of users and businesses. Generative Artificial Intelligence (AI) emerges as a transformative solution, offering advanced capabilities to enhance web engineering models and methodologies. This book presents a timely exploration of how Generative AI can revolutionize the web engineering discipline, providing insights into future challenges and societal impacts.

Generative AI for Web Engineering Models offers a comprehensive examination of integrating AI-driven generative approaches into web engineering practices. It delves into methodologies, models, and the transformative impact of Generative AI on web-based systems and applications. By addressing topics such as web browser technologies, website scalability, security, and the integration of Machine Learning, this book provides a roadmap for researchers, scientists, postgraduate students, and AI enthusiasts interested in the intersection of AI and web engineering.

Through insightful analysis and real-world examples, this book equips readers with the knowledge and tools to navigate the complexities of web engineering in the AI era. It offers practical strategies for leveraging Generative AI to develop more efficient, scalable, and secure web-based solutions. As the digital landscape continues to evolve, Generative AI for Web Engineering Models is a valuable resource for those seeking to stay at the forefront of web technology.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Code Generation
  • Meb ML
  • Nature Language Processing (NLP)
  • Security
  • UML Web Application Extension
  • UML-Based Web Engineering
  • Web Applications
  • Web Architect
  • Web-Browser
  • Website Scalability
  • Websites Scaling
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Editor/Author Biographies

Imdad Ali Shah Research Interests: Cyber Security, AI, ML and Healthcare

Noor Zaman Jhanjhi (NZ Jhanjhi) is currently working as Associate Professor, Director Center for Smart society 5.0 [CSS5], & Cluster Head for Cybersecurity, at the School of Computer Science and Engineering, Taylor’s University, Malaysia. He is supervising a great number of Postgraduate students, mainly in cybersecurity for Data Science. Dr Jhanjhi serves as Associate Editor and Editorial Assistant Board for several reputable journals, received Outstanding Associate Editor Award for IEEE ACCESS for 2020, PC member for several conferences, guest editor for the reputed journals. He is awarded globally as a top 1% reviewer by Publons (WoS). His collective research Impact factor is 400 plus. He has Patents on his account, edited/authored 35 plus research books published by world-class publishers. He is an external Ph.D./Master thesis examiner/evaluator globally, completed more than 22 internationally funded research grants. Served as a keynote speaker for several conferences, presented Webinars, chaired conference sessions, provided Consultancy internationally. His research areas include Cybersecurity, IoT security, Wireless security, Data Science, Software Engineering, UAVs.
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