ReDaML: A Modeling Language for DO-178C High-Level Requirements in Airspace Systems
Bibliographic record
Abstract
Software development in critical airspace cyber-physical systems is challenging, mainly because of its safety-critical nature. Safety standards and regulations, such as DO-178C, provide guidelines for the development of software to ensure they adhere to the essential safety requirements in the certification processes. The requirements process proposed in the standard, which is responsible for developing the high-level requirements, is one of the most crucial steps in the life cycle since it serves as the basis for the subsequent processes. Having safety as a major concern, specifying safety requirements is of fundamental importance, allowing engineers to evaluate them and propose measures to mitigate the impact of a system failure, which can be catastrophic. In this paper, we present ReDaML, a domain-specific modelling language designed to support the development of safety-critical software systems, focused on the specification of high-level requirements in accordance with the DO-178C guidelines. Finally, a scenario of applying the approach to an UAS collision avoidance system is demonstrated.
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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 | 0.002 | 0.001 |
| 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 | 0.000 |
| 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 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".