MBD, OOT and Code Generation: A Cost-Effective Way to Speed Up HMI 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
<div class="section abstract"><div class="htmlview paragraph">This white paper explains the benefits of the Model-Based Design (MBD) approach and Object-Oriented Technology (OOT) that DO-178C provides. It also specifically focuses on the usage of Models and COTS Qualifiable tools that automate or facilitate the verification and validation of avionics applications constructed from Models in order to ensure that there is no unintended function.</div><div class="htmlview paragraph">Software running in Aircraft cockpits has dramatically increased in complexity since DO-178B's revision in 1992. Furthermore, over the past 20 years, software development methods have made significant leaps forward and DO-178B has begun to show its age with respect to the new technology introduced to facilitate software development.</div><div class="htmlview paragraph">This year the newly revamped DO-178C standard sets the certification process record straight by embracing modern technology. DO-178C does not only solidify its foundation by clarifying its core document but also builds the infrastructure to support modern software development techniques already commonly used in avionics development for at least a decade. Fortunately, DO-178C upgrades and clarifies DO-178B. DO-178C therefore considers four techniques of contemporary software development practices which are published as supplements to the core document: 1. Software Tool Qualification Considerations (TQC) [DO-330]. 2. Model-Based Design and Verification Supplement (MBDV) [DO-331]. 3. Object-Oriented Technology Supplement (OOT) [DO-332]. 4. Formal Methods Supplement (FM) [DO-333].</div><div class="htmlview paragraph">Organizations can see gains not only in the reduction of the development cycle but also in the overall improvement of the DO-178C certification process; including reduction of schedule and costs, and improvements in the quality and reliability.</div><div class="htmlview paragraph">In the old school of thought, the methodology relies on textual specifications and physical prototypes. That is why the informal Text-Based Design approach is tightly associated with the waterfall methodology where all the textual requirements are manually coded, inspected, and tested on a real embedded system. In this method, changes in any part of the waterfall chain are very costly and time-consuming, leaving almost no room to iterate on the design.</div><div class="htmlview paragraph">By contrast, in the Model-Based Design approach, the specifications are self-contained in the Human Machine Interface (HMI) Model. The HMI requirements are defined in an unambiguous way and often captured in a formal definition language. Model-Based Design offers a collaborative approach to avionics development and allows engineers to inexpensively experiment with various concepts by deferring hardware integration until much later in the development process. Correcting problems in the early modeling phase is undeniably the strongest argument in favor of the Model-Based Design approach for developing certifiable or non-certifiable avionics applications.</div><div class="htmlview paragraph">This white paper is based on "MBD &amp; Code Generation: A Cost-Effective Way to Speed up HMI Certification," by Luc Marcil, Presagis, Montréal, Québec (Canada) which was presented at the 30th Digital Avionics Systems Conference in October 18th, 2011. © 2011 IEEE.</div></div>
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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