A study of variability spaces in open source software
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
Configurable software systems allow users to customize them according to their needs. Supporting such variability is commonly divided into three parts: configuration space, build space, and code space. In this research abstract, we describe our work in exploring what information these spaces contain in practice, and if this information is consistent. This involves investigating how these spaces work together to ensure that variability is correctly implemented, and to avoid any inconsistencies or anomalies. Our work identifies how variability is implemented in several configurable systems, and initially focuses on less studied parts such as the build system. Our goals include: 1) investigating what information each space provides, 2) quantifying the variability in the build system, 3) studying the effect of build system constraints on variability anomalies, and 4) analyzing how variability anomalies are introduced and fixed. Achieving these goals would help developers make informed decisions when designing variable software, and improve maintainability of existing configurable systems.
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.
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 | 0.001 | 0.005 |
| 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 | 0.003 | 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