Bayonet: Artifact for PLDI 2018 Paper on Static Analysis

Artifact for the PLDI 2018 paper 'Bayonet', authored by Timon Gehr of ETH Zurich. The dataset is a research artifact published on paperswithcode, likely containing data related to the paper's experiments. Its specific content, such as row count or file format, is not detailed in the available metadata.

Use Cases

• Benchmarking static analysis tools using Bayesian inference (inferred from domain, verify after download)
• Reproducing or extending the results from the PLDI 2018 paper (inferred from domain, verify after download)
• Developing new probabilistic programming language analyses (inferred from domain, verify after download)

Strengths

• Published on paperswithcode, a platform for machine learning research artifacts.
• Associated with a peer-reviewed PLDI 2018 conference paper from ETH Zurich.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Row count, file formats, and column definitions are unknown.
• License is listed as 'closed', which may restrict usage.

Provenance

Source

Timon Gehr, ETH Zurich

Collection Method

Created as a research artifact for the PLDI 2018 paper.