An Empirical Study on Inconsistent Changes to Code Clones at Release Level
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
Current research on code clones tries to address the question whether or not code clones are harmful for the quality of software. As most of these studies are based on the fine-grained analysis of inconsistent changes at the revision level, they capture much of the chaotic and experimental nature inherent to any ongoing software development process. Conclusions drawn from the inspection of highly fluctuating and short-lived clones are likely to exaggerate the ill effects of inconsistent changes. To gain a broader perspective, we perform an empirical study on the effect of inconsistent changes on software quality at the release level. Based on a case study on two open source software systems, we observe that only 1% to 3% of inconsistent changes to clones introduce software defects, as opposed to substantially higher percentages reported by other studies. Our findings suggest that developers are able to effectively manage and control the evolution of cloned code at the release level.
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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 | 0.000 |
| 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 | 0.001 | 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