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Introduction:

Artificial Intelligence (AI) has revolutionized the way software development is conducted, particularly in the area of requirements elicitation. AI-driven software requirements elicitation involves the use of intelligent systems to automate the process of gathering, analyzing, and documenting software requirements from stakeholders. This thesis aims to explore the application of AI in software requirements elicitation and its impact on the efficiency and effectiveness of the software development process.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter 2: Literature Review
2.1 Overview of Software Requirements Elicitation
2.2 Traditional Methods of Requirements Elicitation
2.3 Challenges in Requirements Elicitation
2.4 Introduction to Artificial Intelligence
2.5 AI Techniques in Software Development
2.6 AI Applications in Requirements Engineering
2.7 Benefits of AI-driven Requirements Elicitation
2.8 Case Studies on AI-driven Requirements Elicitation
2.9 Challenges and Limitations of AI in Requirements Elicitation
2.10 Future Trends in AI-driven Requirements Elicitation

Chapter 3: System Design and Methodology
3.1 Research Methodology
3.2 Data Collection Techniques
3.3 AI Models for Requirements Elicitation
3.4 System Architecture Design
3.5 Implementation Details
3.6 Evaluation Metrics
3.7 Testing and Validation
3.8 Ethical Considerations

Chapter 4: System Implementation
4.1 Tools and Technologies Used
4.2 Data Preprocessing Techniques
4.3 Model Training and Optimization
4.4 Integration with Existing Systems
4.5 User Interface Design
4.6 Performance Evaluation
4.7 Results Analysis
4.8 Challenges Faced during Implementation

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Contributions of the Study
5.3 Future Research Directions
5.4 Conclusion

Thesis Overview:

The field of software requirements elicitation has seen significant advancements with the integration of AI technologies. This thesis aims to explore the application of AI-driven software requirements elicitation and its impact on the software development process. The study begins with an introduction to the topic, providing a background of the study, problem statement, objectives, limitations, scope, significance, and definition of terms.

The literature review in Chapter 2 provides an overview of traditional methods of requirements elicitation, challenges in the process, introduction to AI, AI techniques in software development, AI applications in requirements engineering, benefits, case studies, challenges, and future trends of AI-driven requirements elicitation.

Chapter 3 focuses on the system design and methodology, discussing research methodology, data collection techniques, AI models, system architecture, implementation details, evaluation metrics, testing, validation, and ethical considerations. The subsequent chapter, System Implementation, delves into tools, technologies, data preprocessing, model training, integration, UI design, performance evaluation, results analysis, and implementation challenges.

The thesis culminates in Chapter 5 with a comprehensive conclusion and summary, highlighting the study’s findings, contributions, future research directions, and concluding remarks. The exploration of AI-driven software requirements elicitation in this thesis provides valuable insights into the potential of AI in enhancing the efficiency and effectiveness of software development processes.

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