AI Code Reviewer

Project Overview

In modern development teams, code review is a critical but time-consuming process. This AI-powered assistant helps streamline reviews by automatically analyzing code changes and providing intelligent feedback.

User Stories

1. As a developer, I want to:

   • Get instant feedback on my code changes
   • Receive suggestions for code improvements
   • Learn about potential security issues
   • See examples of better code patterns
   • Track my code quality over time

2. As a team lead, I want to:

   • Ensure consistent code quality across the team
   • Reduce time spent on routine code reviews
   • Monitor team-wide code metrics
   • Customize rules for our project needs
   • Generate code quality reports

3. As a security engineer, I want to:

   • Catch security vulnerabilities early
   • Enforce security best practices
   • Track security-related metrics
   • Integrate with security scanning tools
   • Generate security compliance reports

Example Code

from transformers import CodeBertTokenizer, CodeBertForSequenceClassification
import torch

class AICodeReviewer:
    def __init__(self):
        self.tokenizer = CodeBertTokenizer.from_pretrained('microsoft/codebert-base')
        self.model = CodeBertForSequenceClassification.from_pretrained('microsoft/codebert-base')

    def analyze_code(self, code_snippet):
        inputs = self.tokenizer(code_snippet, return_tensors='pt', truncation=True)
        outputs = self.model(**inputs)
        predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
        return self.generate_feedback(predictions)