Data for 'Less is More': Supporting Vulnerability Detection in Code Review

Data and material supporting the academic paper 'Less is More: Supporting Developers in Vulnerability Detection during Code Review'. The dataset was created by Larissa Braz at the University of Zurich. The specific size, format, and temporal coverage are not detailed in the available metadata.

Use Cases

• Training machine learning models for vulnerability detection based on code review artifacts mentioned in the description
• Analyzing developer behavior and effectiveness during security-focused code reviews based on the supporting material
• Benchmarking tools that aim to support developers in identifying vulnerabilities during code review

Strengths

• Data is directly linked to a peer-reviewed academic paper, providing research context.
• The dataset originates from a recognized academic institution, the University of Zurich.

Limitations

• Row count and file size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of Zurich

Collection Method

Created as supporting material for an academic paper.