Bibliographic record
Abstract
Understanding the structure of large existing (and evolving) software systems is a major challenge for software engineers. In reverse engineering, we aim to compute, for a given software system, a decomposition of the system into its subsystems. CCVisu is a lightweight tool that takes as input a software graph model and computes a visual representation of the system's structure, i.e., it structures the system into separated groups of artifacts that are strongly related, and places them in a 2- or 3-dimensional space. Besides the decomposition into subsystems, it reveals the relatedness between the subsystems via interpretable distances. The tool reads a software graph from a simple text file in RSF format, e.g., call, inheritance, containment, or co-change graphs. The resulting system structure is currently either directly presented on the screen, or written to an output file in SVG, VRML, or plain text format. The tool is designed as a reusable software component, easy to use, and easy to integrate into other tools; it is based on efficient algorithms and supports several formats for data interchange.
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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".