DScribe: Co-generating Unit Tests and Documentation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Test suites and documentation capture similar information despite serving distinct purposes. Such redundancy introduces the risk that the artifacts inconsistently capture specifications. We present DScribe, an approach that leverages the redundant information in tests and documentation to reduce the cost of creating them and the threat of inconsistencies. DScribe allows developers to define simple templates that jointly capture the structure to test and document a specification. They can then use these templates to generate consistent and checkable tests and documentation. By linking documentation to unit tests, DScribe ensures documentation accuracy as outdated documentation is flagged by failing tests. DScribe’s template-based approach also enforces a uniform style throughout the artifacts. Hence, in addition to reducing developer effort, DScribe improves artifact quality by ensuring consistent content and style. Video: https://www.youtube.com/watch?v=CUKp3-MjMog
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it