A study of refactorings during software change tasks
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
Abstract Developers frequently undertake software change tasks that could be partially or fully automated by refactoring tools. As has been reported by others, all too often, these refactoring steps are instead performed manually by developers. These missed opportunities are referred to as occasions of disuse of refactoring tools. We perform an observational study in which 17 developers with professional experience attempt to solve three change tasks with steps amenable to the use of refactoring tools. We found that the strategies developers use to approach these tasks shape their workflow, which, in turn, shape the opportunities for refactoring tool use. We report on a number of findings about developer strategies, demonstrating the difficulty of aligning the kind of refactoring steps that emerge during a change task based on the strategy with the tools available. We also report on findings about refactoring tools, such as the difficulties developers face in controlling the scope of application of the tools. Our findings can help inform the designers of refactoring tools.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it