{"url":"/dataset/detection-of-the-fire-drill-anti-pattern-nine","name":"Fire Drill Anti-Pattern Dataset","full_name":null,"description_markdown":"**Fire Drill Anti-Pattern Dataset** is a collection of nine real-world software projects for detection of the fire drill anti-pattern with ground truth, issue-tracking data, source code density, models and code. The data is supposed to aid the detection of the presence of the Fire Drill anti-pattern. It includes data, ground truth, code, and notebooks. The data supports two distinct methods of detecting the AP: a) through issue-tracking data, and b) through the underlying source code. Therefore, this package includes the following:\r\n\r\nFire Drill in issue-tracking data:\r\n\r\n* __Ground truth__ for whether and how strong each project exhibits the Fire Drill AP, on a scale from [0,10]. This was determined by two individual raters, who also reached a consensus.\r\n* Coefficients for indicators for the first method, per project.\r\n* Detailed issue-tracing data for each project: what occurred and when.\r\n* Time logs for each project.\r\n\r\nFire Drill in source-code data:\r\n\r\n* Three technical reports that document the developed method of how to translate a description into a detectable pattern, and to use the pattern to detect the presence and to score it (similar to the rating). Also includes a report for how activities were assigned to individual commits.\r\n* Source code density data (metrics) for each commit in each of the nine projects as a separate dataset.\r\n* Code: a snapshot of the repository that holds all code, models, notebooks, and pre-computed results, for utmost reproducibility (the code is written in R).","description_withheld":null,"homepage":"https://doi.org/10.5281/zenodo.4734053","introduced_date":"2021-05-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/technical-reports-compilation-detecting-the","title":"Technical Reports Compilation: Detecting the Fire Drill Anti-pattern Using Source Code and Issue-Tracking Data","first_author":"Sebastian Hönel","url":null},"license":{"name":"Creative Commons Attribution Non Commercial Share Alike 4.0 International","url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode"},"modalities":[],"tasks":[],"languages":[],"variants":["Fire Drill Anti-Pattern Dataset"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}