Intelligent Requirements Engineering with Fuzzy Logic and AI
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Requirements Engineering is fundamental to successful software development, yet traditional methods often fail to capture the dynamic, uncertain, and ambiguous needs of stakeholders. This challenge inspired us to write this book, introducing Intelligent Requirements Engineering, a paradigm that integrates fuzzy logic, machine learning, and artificial intelligence to enhance requirements modeling and design. The growing demands of domains such as healthcare, finance, e-governance, and cloud computing require adaptive, explainable, and resilient requirements. Fuzzy modeling helps address vaguene...
Requirements Engineering is fundamental to successful software development, yet traditional methods often fail to capture the dynamic, uncertain, and ambiguous needs of stakeholders. This challenge inspired us to write this book, introducing Intelligent Requirements Engineering, a paradigm that integrates fuzzy logic, machine learning, and artificial intelligence to enhance requirements modeling and design. The growing demands of domains such as healthcare, finance, e-governance, and cloud computing require adaptive, explainable, and resilient requirements. Fuzzy modeling helps address vagueness, while AI and NLP techniques add automation, scalability, and predictive strength. The book is structured into eight chapters, moving from foundations of intelligent modeling to case studies, ethical aspects, and future research directions. Each chapter balances theory with application, offering frameworks, methodologies, and examples with real-world relevance. We believe this work will benefit researchers, students, and practitioners aiming to adopt AI-driven RE tools in industry.
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