AI-Driven and Traditional Code Review

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AI-Driven and Traditional Code Review
Student: Maksim Pershin
Group: 423-2
Teacher: E.R. Mengardt.

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Presentation plan
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Introduction to the code review.
AI tools: opportunities.
Traditional methods: pros and cons.
Comparison of approaches
Personal Experience
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Introduction to the code review
AI-driven code analysis is the use of AI algorithms to evaluate
and enhance code quality in software development, automating
the code review process.
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AI tools: opportunities
Artificial Intelligence offers the following advantages over
traditional methods:
1. Increased accuracy
2. Faster review speed
3. Continuous improvement
4. Enhanced efficiency
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Traditional methods: advantages
Manual code review involves developers manually inspecting
each other’s code, consuming significant developer hours.
Advantages:
1. Control
2. Fosters team professional development.
3. Encourages accountability.
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Traditional methods: disadvantages
Challenges:
1. Time-consuming process.
2. Subjectivity in code quality assessments.
3. Risk of missing errors or optimization opportunities.
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Comparison of approaches
Criteria
AI-Driven
Traditional
Collaborative Approach
Speed
Instant code analysis.
Depends on expert
availability.
Fast AI checks + deep
expertise.
Context
Limited understanding of
logic.
Deep analysis of code
intent.
AI detects errors; humans
explain context.
Learning
Automated examples.
Mentorship and feedback.
AI prompts + live
discussion.
Flexibility
Standardized solutions.
Creative approaches.
AI handles routine;
humans tackle complex.
Risks
Algorithm dependency.
Subjectivity and human
bias.
Minimizing drawbacks
through balance.
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Personal Experience
During my university studies, I have often used and continue to
use it for tasks like checking my programs for the ObjectOriented Programming course or writing code in C.
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Link to the information source
Conclusion:
Use AI cautiously, as machines
cannot replace human creativity,
but AI can significantly save time
in code review.
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