Clone Swarm: A Cloud Based Code-Clone Analysis Tool
Bibliographic record
Abstract
A code clone is defined as a pair of similar code fragments within a software system. While code clones are not always harmful, they can have a detrimental effect on the overall quality of a software system due to the propagation of bugs and other maintenance implications. Because of this, software developers need to analyse the code clones that exist in a software system. However, despite the availability of several clone detection systems, the adoption of such tools outside of the clone community remains low. A possible reason for this is the difficulty and complexity involved in setting up and using these tools. In this paper, we present Clone Swarm, a code clone analytics tool that identifies clones in a project and presents the information in an easily accessible manner. Clone Swarm is publicly available and can mine any open-sourced GIT repository. Clone Swarm internally uses NiCad, a popular clone detection tool in the cloud and lets users interactively explore code clones using a web-based interface at multiple granularity levels (Function and Block level). Clone results are visualized in multiple overviews, all the way from a high-level plot down to an individual line by line comparison view of cloned fragments. Also, to facilitate future research in the area of clone detection and analysis, users can directly download the clone detection results for their projects. Clone Swarm is available online at clone-swarm.usask.ca. The source code for Clone Swarm is freely available under the MIT license on GitHub.
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.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".