Fraunhofer-AISEC/cpg
Oct 2025 – Oct 2025
1 Month active
Languages Used
JavaKotlin
Technical Skills
Abstract InterpretationCompiler DesignData Flow AnalysisJavaKotlinStatic Analysis
Robert Haimerl
PROFILE
Robert Haimerl
Robert Haimerl developed an abstract value analysis feature for the Fraunhofer-AISEC/cpg repository, focusing on enhancing static analysis precision within the Code Property Graph framework. He implemented interval analysis for integers and collection sizes, introducing lattice structures and evaluators for value types using Java and Kotlin. His approach leveraged abstract interpretation and data flow analysis to enable more accurate reasoning about code properties, supporting earlier bug detection and improved security analysis. Extensive test coverage was built to validate the reliability of the new analysis capabilities. The work demonstrated depth in compiler design and static analysis, addressing core challenges in code reasoning.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
5,107
Activity Months1
Your Network
143 people
Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025October 2025: Delivered Abstract Value Analysis for the Code Property Graph (CPG) in Fraunhofer-AISEC/cpg. Implemented interval analysis for integers and collection sizes within the CPG framework, introducing lattice structures, evaluators for value types, and extensive tests to validate static analysis capabilities. This work enhances precision of static analysis, enabling earlier bug detection, improved security posture, and more reliable code-property reasoning for developers and security analysts.
1 Commits • 1 Features
Oct 1, 2025October 2025: Delivered Abstract Value Analysis for the Code Property Graph (CPG) in Fraunhofer-AISEC/cpg. Implemented interval analysis for integers and collection sizes within the CPG framework, introducing lattice structures, evaluators for value types, and extensive tests to validate static analysis capabilities. This work enhances precision of static analysis, enabling earlier bug detection, improved security posture, and more reliable code-property reasoning for developers and security analysts.
October 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture100.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaKotlin
Technical Skills
Abstract InterpretationCompiler DesignData Flow AnalysisJavaKotlinStatic AnalysisSymbolic Execution
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