The Linux kernel: a case study of build system variability
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
SUMMARY Although build systems control what code gets compiled into the final built product, they are often overlooked when studying software variability. The Linux kernel is one of the biggest open source software systems supporting variability and contains over 10,000 configurable features described in its Kconfig files. To understand the role of the build system in variability implementation, we use Linux as a case study. We study its build system, Kbuild , and extract the variability constraints in its Makefiles. We first provide a quantitative analysis of the variability in Kbuild . We then study how the variability constraints in the build system affect variability anomalies detected in Linux. We concentrate on dead and undead artifacts, and by extending previous work, we show that considering build system variability constraints allows more anomalies to be detected. We provide examples of such anomalies on both the code block and source file level. Our work shows that Kbuild contains a large percentage of the variability information in Linux, so it should not be ignored during variability analysis. Nonetheless, the anomalies we find suggest that variability on the file level in Kbuild is consistent with Kconfig , whereas the constraints on the code level are harder to keep consistent with both Kbuild and Kconfig . Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.002 | 0.002 |
| 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 | 0.000 | 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