On the Exploration of Model-Based Support for DO-178C-Compliant Avionics Software Development and Certification
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
Vital functions of avionics systems nowadays depend highly on software. Engineering such safety-critical software is not straightforward as authorities impose stringent regulation like DO-178. Besides, the more functions the software has to provide, the more complex it becomes. Thus, effective engineering methods are required. In this context, DO-178C now considers contemporary software development techniques like Model-Driven Engineering. In particular Model-Driven Engineering has gained interest as a cost-and time-effective alternative reducing software development complexities by enabling reasoning at the model level. In this paper we present a review of a set of model-based approaches to assess their support for software development and certification under DO-178C. We built a framework to characterize these approaches according with several criteria, specially coverage of DO-178C's required information for compliance. We analyze the approaches using this framework and highlight their commonalities, differences, strengths and weaknesses. Additionally, we identify open issues on which research may focus.
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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 | 0.000 | 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 | 0.000 |
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