An Analysis of Library Usage in the C++ Code Base of Fedora Linux 37
Bibliographic record
Abstract
Several aspects of library usage in C++ are explored. A framework is proposed for analyzing the C++ code base of Linux distributions that employ the DNF package manager, such as Fedora Linux and Red Hat Enterprise Linux. This framework is used in conjunction with a C++ source-code analysis tool (developed by the authors) to study library usage with a fine level of granularity, considering instances of uses of types, type aliases, member/nonmember functions, variables, and enumerators. The effectiveness of our proposed framework and C++ analysis tool is demonstrated by applying them to the C++ code base of Fedora Linux 37. Using this approach, we were able to analyze library usage in the C++ source code of over 2300 software packages. Numerous observations are made about various aspects of library usage that can facilitate improved teaching of C++, allow more effective design/implementation of C++ libraries, and help to direct the future evolution of the C++ standard.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".