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Why iCR
Accuracy
Generates accurate fixes not suggestions
Precision
Generates low false positive rate. ICR < 3% vs.others >50%
Quality
Increase code quality automatically at lower cost
Productivity
Improves developer productivity by 11%
Innovation
Focuses resources on features instead of bug fixing
What Drives iCR
iCR reduces to practice cutting-edge research done in three prominent disciplines.
Deep Static Analysis
Deep pointer analysis creates accurate knowledge vital to code repairing
Machine Intelligence
Machines learn from your code to generate fixes as if done by a human developer
Code Refactoring
Behavior enhancing refactoring transformations fix problems while preserving original behavior
How it works
Cloud Platform
- Runs on AWS EC2 and Azure instances
- Accesses source code securely using GitHub, GitLab or BitBucket.
- Fixes turned into pull requests
Private Platform
- Securely runs on your on-premise servers using Docker
- Access source code from private repositories
- Easy to use interface
What it fixes
71 Fixers of iCR for Java cover
- Arithmetic Issues
- Concurrency Issues
- Improper Access Control
- Logical Bugs
- Null Pointer Issues
- Weak Cryptography Issues
69 Fixers of iCR for Python cover
- Arithmetic Issues
- Improper Access Control
- Logical Bugs
- Security Misconfiguration Issues
- Sensitive Data Exposure
- Weak Cryptography Issues
44 Fixers of iCR for C cover
- Buffer Overflow
- Integer Arithmetic Issues
- Logical Bugs
- Memory Leak Issues
- Null Pointer Issues
- Security Misconfiguration Issues