GraphCanon updated Oct 8, 2026 · GitHub synced Oct 8, 2026
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Decision brief
RepoBench assesses repository-level code auto-completion systems, offering benchmarks crucial for researchers and developers working on similar systems.
Good fit when
- Use RepoBench if you are evaluating the performance of your own repository-level code completion system against established benchmarks.
- Consider RepoBench when you need data insights specific to the effectiveness of your auto-completion algorithms at a repository level.
Avoid when
- Do not use RepoBench if your focus is on line-level or function-level code completions as opposed to repository-wide assessments.
- Avoid RepoBench in scenarios where you require real-time analytics rather than benchmarking against static datasets and predefined criteria.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (782d since push)
- As of Oct 8, 2026
- Provenance
- Not a fork · Personal account
- As of Oct 8, 2026
- Security (OSV)
- No criticals
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install repobenchSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
RepoBench evaluates performance of repository-level code auto-completion systems providing benchmarks for researchers and developers.
Capability facts
- Languages
- python
Source: github.language · Oct 8, 2026
Categories
Tags
README
🛠️ Installation [!NOTE] There is a file, which contains dependencies for reproducing the results in the paper. If you are only interested in the data, you can skip the installation of dependencies.
For agents
This page has a .md twin and JSON over the API.