An Empirical Study of Function Clones in Open Source Software
Why this work is in the frame
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Bibliographic record
Abstract
The new hybrid clone detection tool NICAD combines the strengths and overcomes the limitations of both text-based and AST-based clone detection techniques to yield highly accurate identification of cloned code in software systems. In this paper, we present a first empirical study of function clones in open source software using NICAD. We examine more than 15 open source C and Java systems, including the entire Linux Kernel and Apache httpd, and analyze their use of cloned code in several different dimensions, including language, clone size, clone location and clone density by proportion of cloned functions. We manually verify all detected clones and provide a complete catalogue of different clones in an online repository in a variety of formats. These validated results can be used as a cloning reference for these systems and as a benchmark for evaluating other clone detection 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 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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