Static Analysis Results for 50 Open Source Applications

50 open source software applications from GitHub were analyzed using SonarQube, PMD, CKJM Extended, and Findbugs tools. This dataset supports empirical research into the relationship between technical debt and software security. The data was created for a 2019 academic publication by researchers from Imperial College London.

Use Cases

• Correlating technical debt metrics with security vulnerability indicators across multiple projects.
• Training machine learning models to predict software defects based on static code analysis results.
• Benchmarking the output of different static analysis tools (SonarQube, PMD, Findbugs) on a common set of applications.
• Analyzing the prevalence and types of code issues in a sample of open source software.

Strengths

• Contains results from four established static analysis tools (SonarQube, PMD, CKJM Extended, Findbugs).
• Based on a defined sample of 50 open source applications, providing a multi-project perspective.
• Has associated peer-reviewed academic publication, providing context and validation.

Limitations

• Specific column names, row counts, and dataset size are not provided in the available metadata.
• The dataset's last update date is unknown, which may affect relevance for contemporary tool comparisons.
• Limited to 50 applications, which may not be representative of all software domains.

Provenance

Source

Miltiadis Siavvas (Imperial College London) and co-authors.

Collection Method

Static analysis of 50 open source software applications retrieved from GitHub using SonarQube, PMD, CKJM Extended, and Findbugs.