Table of Contents

Chapter 1: Introduction
1.1 Background of Study
1.2 Problem Statement
1.3 Objective of Study
1.4 Limitation of Study
1.5 Scope of Study

Chapter 2: Literature Review
2.1 Automated Code Review Systems
2.2 Machine Learning in Software Development
2.3 Benefits of Automated Code Review Systems
2.4 Existing Automated Code Review Systems

Chapter 3: System Design
3.1 System Architecture
3.2 Data Collection and Processing
3.3 Machine Learning Algorithms Selection
3.4 User Interface Design

Chapter 4: Implementation
4.1 Data Preparation
4.2 Model Training and Evaluation
4.3 System Integration
4.4 Testing and Validation

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Contributions to the Field
5.3 Future Work
5.4 Conclusion

Project Summary

Title: Automated Code Review System using Machine Learning

The final year project aims to develop an Automated Code Review System using Machine Learning to assist software developers in reviewing and improving the quality of their code. The system will utilize machine learning algorithms to analyze and detect coding errors, bugs, and potential vulnerabilities in the code.

The project will begin with a thorough literature review on automated code review systems and the role of machine learning in software development. The system design phase will involve designing the architecture, data collection methods, machine learning algorithm selection, and user interface design.

During the implementation phase, data will be prepared, machine learning models will be trained and evaluated, and the system will be integrated, tested, and validated. The final chapter will provide a summary of findings, contributions to the field, suggestions for future work, and a conclusion.

Overall, the project aims to provide a valuable tool for software developers to improve the quality of their code and enhance the efficiency of code review processes.

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