SPCP-Miner: A tool for mining code clones that are important for refactoring or tracking
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
Code cloning has both positive and negative impacts on software maintenance and evolution. Focusing on the issues related to code cloning, researchers suggest to manage code clones through refactoring and tracking. However, it is impractical to refactor or track all clones in a software system. Thus, it is essential to identify which clones are important for refactoring and also, which clones are important for tracking. In this paper, we present a tool called SPCP-Miner which is the pioneer one to automatically identify and rank the important refactoring as well as important tracking candidates from the whole set of clones in a software system. SPCP-Miner implements the existing techniques that we used to conduct a large scale empirical study on SPCP clones (i.e., the clones that evolved following a Similarity Preserving Change Pattern called SPCP). We believe that SPCP-Miner can help us in better management of code clones by suggesting important clones for refactoring or tracking.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| 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