Generative Ai For Web Engineering Models
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Generative AI for Web Engineering Models
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.
Generative AI in Software Engineering
Author: Aguilar-Calderón, José Alfonso
language: en
Publisher: IGI Global
Release Date: 2025-06-13
Generative AI transforms the landscape of software engineering, enabling automation, creativity, and efficiency throughout development. By leveraging advanced machine learning models, like large language models and code generation tools, developers can automate code generation, streamline testing, and design software architectures. This shift accelerates development timelines and redefines the roles of engineers and the skills required in modern software teams. As generative AI evolves, its integration into software engineering raises important questions around reliability, security, and human-AI collaboration. Generative AI in Software Engineering explores the evolving role of generative AI in the software engineering landscape. It examines how AI accelerates software development, reduces costs, and enhances creativity, offering real-world benefits for businesses. This book covers topics such as quantum computing, visual intelligence, and environment science, and is a useful resource for business owners, computer engineers, academicians, researchers, and data scientists.
Handbook of AI-Driven Threat Detection and Prevention
In today’s digital age, the risks to data and infrastructure have increased in both range and complexity. As a result, companies need to adopt cutting-edge artificial intelligence (AI) solutions to effectively detect and counter potential threats. This handbook fills the existing knowledge gap by bringing together a team of experts to discuss the latest advancements in security systems powered by AI. The handbook offers valuable insights on proactive strategies, threat mitigation techniques, and comprehensive tactics for safeguarding sensitive data. Handbook of AI-Driven Threat Detection and Prevention: A Holistic Approach to Security explores AI-driven threat detection and prevention, and covers a wide array of topics such as machine learning algorithms, deep learning, natural language processing, and so on. The holistic view offers a deep understanding of the subject matter as it brings together insights and contributions from experts from around the world and various disciplines including computer science, cybersecurity, data science, and ethics. This comprehensive resource provides a well-rounded perspective on the topic and includes real-world applications of AI in threat detection and prevention emphasized through case studies and practical examples that showcase how AI technologies are currently being utilized to enhance security measures. Ethical considerations in AI-driven security are highlighted, addressing important questions related to privacy, bias, and the responsible use of AI in a security context. The investigation of emerging trends and future possibilities in AI-driven security offers insights into the potential impact of technologies like quantum computing and blockchain on threat detection and prevention. This handbook serves as a valuable resource for security professionals, researchers, policymakers, and individuals interested in understanding the intersection of AI and security. It equips readers with the knowledge and expertise to navigate the complex world of AI-driven threat detection and prevention. This is accomplished by synthesizing current research, insights, and real-world experiences.