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Collection of 70 realistically Complex Regression Errors that were systematically extracted from the repositories and bug reports of four open-source software projects: Make, Grep, Findutils, and Coreutils.
Activity such as commits, stars, prices, and market cap of over 200 cryptocurrency projects on GitHub over time. Raw, historic data is also [available](https://zenodo.org/record/2595588#.XRuzuBNKhSM).
The dataset contains the analysis results of 5 open source software quality tools eslint, escomplex, nsp, jsinspect and sonarjs for 2000 popular (in terms of stars and downloads) npm packages.
Graph of the development history and file metadata of >80 million software projects from various forges (GitHub, Gitlab, Debian, PyPI, Google Code, etc) in a deduplicated and unified representation ([paper here](https://dl.acm.org/citation.cfm?id=3341907)).
SWE-bench is a benchmark designed to evaluate the ability of AI models to solve real-world software engineering problems by generating fixes for issues found in open-source code repositories.
Static source code based datasets which includes the Bugcatchers Bug Dataset, the [Bug Prediction Dataset](http://bug.inf.usi.ch/index.php), the [Eclipse Bug Dataset](https://www.st.cs.uni-saarland.de/softevo/bug-data/eclipse/), the [GitHub Bug Dataset](http://www.inf.u-szeged.hu/~ferenc/papers/GitHubBugDataSet/), some datasets from the [PROMISE](http://promise.site.uottawa.ca/SERepository/datasets-page.html) repository.
Java tools and infrastructure to resolve the whole Maven dependency graph, hosted in Maven Central, in the form of a [Neo4j](https://neo4j.com/) Graph.
Python tool to compute a score for a repository from GHTorrent. The score quantifies the extent to which the project contained within the repository is _engineered_.