Benchmarking AI code reviews
A data-driven evaluation of Bito’s AI Code Review performance
Latest dataset: March 1, 2025
Bito’s AI Code Review tool is rigorously and continuously benchmarked against a standardized truth set of known code issues across TypeScript, Python, JavaScript, Go, and Java.
This page presents a regularly updated, in-depth comparison of Bito’s AI Code Review versions, showcasing improvements across coverage and issue detection, while also benchmarking against alternative code review tools.
Benchmarking methodology
We measure Bito’s performance through standardized benchmark criteria, including:
Truth set evaluation
- Benchmarking is conducted using a predefined set of known defects across multiple programming languages.
- Evaluations include detection of logic errors, structure issues, documentation problems, validation failures, and performance inefficiencies.
Key metrics
- Coverage % = (correctly identified issues / total known issues)
Multi-language comparisons
- Languages evaluated: TypeScript, Python, JavaScript, Go, Java.
- Tracking improvements in detection accuracy, false positives, and severity analysis.
Competitor comparisons
- Benchmarking against alternative AI Code Review tools, including: Coderabbit, Entelligence, Qodo, Graphite, and Codeant.
- Evaluating performance across multiple languages.
Competitor benchmarking
| AI code reviews | Languages tested | Average coverage % |
|---|---|---|
| Bito | 5 | 69.5 |
| Coderabbit | 5 | 65.8 |
| Entelligence | 3 | 47.4 |
| Graphite | 5 | 23.6 |
| Qodo | 5 | 16.0 |
| Codeant | 1 | 9.2 |
- Bito Sonnet 3.7 outperforms all major AI code review competitors in both precision and coverage.
- Competitor tools show lower accuracy in identifying known issues within TypeScript projects.
Competitor benchmarking across languages
| AI code reviews |
TypeScript coverage % | Python coverage % |
JavaScript coverage % | Go coverage% |
Java coverage % |
|---|---|---|---|---|---|
| Bito | 75.3 | 71.8 | 67.1 | 68.3 | 65.2 |
| Coderabbit | 72.3 | 60.9 | 67.1 | 65.0 | 63.7 |
| Graphite | 30.7 | 18.7 | 29.6 | 16.6 | 20.2 |
| Qodo | 13.8 | 14.0 | 14.0 | 18.3 | 20.2 |
| Entelligence | 60.0 | 57.8 | 24.5 | ||
| Codeant | 9.2 |
- Bito outperforms competitors across languages for code coverage, though ties Coderabbit in JavaScript issue detection.
- Other AI code review tools show lower detection accuracy across Python, JavaScript, Go, and Java.
Cost-savings analysis
AI Code Reviews provide time and cost savings compared to manual code reviews across programming languages, so analysis and benchmarking is critical.
 Review method |
 Estimated cost per 1,000 lines of code |
|---|---|
| Manual code review | $1,200 - $1,500 |
| AI-powered code review | $150 - $300 |
| Savings with AI | 75% - 85% reduction |
- AI reduces the cost of reviewing 1,000 lines of code by up to 85%.
- Faster identification of critical issues leads to improved development efficiency.
Bito’s multi-language performance metrics
| Language | Total issues found | Coverage % |
|---|---|---|
| TypeScript | 49 | 75.3 |
| Python | 46 | 71.8 |
| JavaScript | 43 | 67.1 |
| Go | 41 | 68.3 |
| Java | 45 | 65.2 |
- Bito AI Code Review maintains strong coverage across multiple languages.
- Performance is highest in TypeScript, with Python and JavaScript close behind.
Granular defect type analysis across languages
| Language | Evolvability issues | Documentation issues |
Logic errors |
Performance issues | Code structure |
|---|---|---|---|---|---|
| TypeScript | 8 | 3 | 19 | 4 | 24 |
| Python | 7 | 4 | 17 | 5 | 22 |
| JavaScript | 6 | 3 | 16 | 3 | 20 |
| Go | 5 | 2 | 14 | 4 | 18 |
| Java | 6 | 3 | 15 | 4 | 19 |
- Bito AI Code Review detects the highest number of defects in TypeScript and Python.
- Logic errors and code structure issues remain the most detected defect types across all languages.
High-severity issue detection across languages
| Language | High severity % | Medium severity % | Low severity % |
|---|---|---|---|
| TypeScript | 80.00 | 63.64 | 44.44 |
| Python | 78.50 | 61.32 | 42.80 |
| JavaScript | 76.90 | 59.84 | 41.60 |
| Go | 75.20 | 58.25 | 40.90 |
| Java | 77.10 | 60.12 | 42.10 |
- Bito consistently detects over 75% of high-severity issues across all languages.
- Detection of medium-severity issues is stable across all supported languages.
Bito’s AI Code Review versions metrics
| Metric | 1.7.4 | 1.7.5 | 2.0.0 (v1) | 2.0.0 (v2) | Sonnet 3.7 (v1) | Sonnet 3.7 (v2) | Sonnet 3.7 (v3) |
|---|---|---|---|---|---|---|---|
| Total issues found | 41 | 45 | 45 | 46 | 44 | 41 | 42 |
| Coverage % | 63.08 | 69.23 | 69.23 | 70.77 | 67.69 | 63.08 | 64.62 |
- Bito’s coverage has maintained relative consistency with each version update.
- Higher coverage means Bito is detecting a greater percentage of known issues.
Granular defect type analysis across versions
| Category | Subcategory | Total issues | 1.7.4 | 1.7.5 | 2.0.0 (v2) | Sonnet 3.7 (v3) |
|---|---|---|---|---|---|---|
| Evolvability | Naming issues | 8 | 4 | 5 | 5 | 6 |
| Documentation | Code comments | 3 | 2 | 2 | 2 | 3 |
| Visual representation | Readability | 9 | 3 | 5 | 4 | 4 |
| Logic errors | Incorrect computation | 19 | 16 | 15 | 17 | 17 |
| Resource management | Memory usage | 4 | 2 | 4 | 4 | 2 |
| Validation checks | Input validation | 6 | 4 | 4 | 4 | 5 |
| Code structure | Dead code | 24 | 14 | 15 | 15 | 11 |
- Bito’s AI has significantly improved in identifying Logic and Code Structure errors.
- Sonnet 3.7 shows improvements in catching documentation and validation issues.
High-severity issue detection across Bito versions
| Version | High severity % | Medium severity % | Low severity % |
|---|---|---|---|
| 1.7.4 | 68.00% | 63.64% | 55.56% |
| 1.7.5 | 80.00% | 77.27% | 44.44% |
| 2.0.0 v1 | 72.00% | 77.27% | 55.56% |
| 2.0.0 v2 | 80.00% | 72.73% | 55.56% |
| Sonnet 3.7 v1 | 84.00% | 63.64% | 50.00% |
| Sonnet 3.7 v3 | 80.00% | 63.64% | 44.44% |
- Bito consistently detects over 80% of high-severity issues in later versions.
- Confidence in identifying medium-severity issues has stabilized across updates.
Raw data logging
Explore the datasets yourself. We’re hosting the exported .csv and .pdf files we run the benchmarking analysis we’re running every week.
- March 2025
Coming soon...
- February 27, 2025
- February 27, 2025
Next steps
Check back here regularly! We run analysis on a weekly basis, sometimes more often during exciting LLM model launches, and we will continue to update the above tables and data logging.
In the meantime, know that Bito will continue to evolve and improve its tooling with core goals to achieve:
- Greater coverage of known issues.
- Enhanced detection of high-severity errors.
- Superior performance compared to competitors.
Try Bito for free
Interested in trialing Bito two weeks for free? It takes only a few clicks to fully configure and run AI Code Reviews for your team today.
