The impact of cross-distribution bug duplicates, empirical study on Debian and Ubuntu
Bibliographic record
Abstract
Although open source distributions like Debian and Ubuntu are closely related, sometimes a bug reported in the Debian bug repository is reported independently in the Ubuntu repository as well, without the Ubuntu users nor developers being aware. Such cases of undetected cross-distribution bug duplicates can cause developers and users to lose precious time working on a fix that already exists or to work individually instead of collaborating to find a fix faster. We perform a case study on Ubuntu and Debian bug repositories to measure the amount of cross-distribution bug duplicates and estimate the amount of time lost. By adapting an existing within-project duplicate detection approach (achieving a similar recall of 60%), we find 821 cross-duplicates. The early detection of such duplicates could reduce the time lost by users waiting for a fix by a median of 38 days. Furthermore, we estimate that developers from the different distributions lose a median of 47 days in which they could have collaborated together, had they been aware of duplicates. These results show the need to detect and monitor cross-distribution duplicates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".