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Introduction

In recent years, with the rapid development of technology, software engineering has become increasingly popular. As software development continues to grow, the need for automated code review systems has become more crucial. Code review is a process where developers check each other’s code for errors, bugs, and style inconsistencies. Traditionally, code review has been done manually, which can be time-consuming and error-prone. To address this challenge, machine learning techniques have been applied to automate the code review process.

This thesis aims to design a system for automated code review using machine learning. The system will leverage machine learning algorithms to analyze and review code, identify potential issues, and provide feedback to developers. By automating the code review process, developers can save time and improve code quality.

The remainder of this thesis is organized as follows:

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 Two: Literature Review
2.1 Overview of Code Review
2.2 Traditional Code Review Process
2.3 Machine Learning in Code Review
2.4 Automated Code Review Systems
2.5 Benefits of Automated Code Review
2.6 Challenges of Automated Code Review
2.7 Related Work
2.8 Gaps in Existing Literature
2.9 Summary of Literature Review

Chapter Three: Research Methodology
3.1 Research Design
3.2 Data Collection
3.3 Data Preprocessing
3.4 Feature Extraction
3.5 Machine Learning Algorithms
3.6 Model Training
3.7 Model Evaluation
3.8 Validation
3.9 Ethical Considerations

Chapter Four: Discussion of Findings
4.1 Overview of Findings
4.2 Analysis of Results
4.3 Comparison with Existing Systems
4.4 Implications of Findings
4.5 Recommendations for Future Research
4.6 Limitations of the Study
4.7 Conclusion

Chapter Five: Conclusion and Summary
5.1 Summary of Findings
5.2 Conclusion
5.3 Contributions to the Field
5.4 Practical Implications
5.5 Future Research Directions
5.6 Final Thoughts

This thesis aims to contribute to the field of automated code review using machine learning by designing a system that can effectively review code and provide valuable feedback to developers. By automating the code review process, developers can improve code quality, enhance productivity, and reduce the likelihood of bugs and errors in software development projects.

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