DEVS for AUTOSAR-based system deployment modeling and simulation
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
AUTOSAR (AUTomotive Open System ARchitecture) is an open and standardized automotive software architecture, developed by automobile manufacturers, suppliers, and tool developers. Its design is a direct consequence of the increasingly important role played by software in vehicles. As design choices during the software deployment phase have a large impact on the behavior of the system, designers need to explore various trade-offs. Examples of such design choices are the mapping of software components to processors, the priorities of tasks and messages, and buffer allocation. In this paper, we evaluate the appropriateness of DEVS, the Discrete-Event System specification, for modeling and subsequent performance evaluation of AUTOSAR-based systems. Moreover, a DEVS simulation model is constructed for AUTOSAR-based electronic control units connected by a communication bus. To aid developers in evaluating a deployment solution, the simulation model is extended with co-simulation with a plant and environment model, evaluation at different levels of detail, and fault injection. Finally, we examine how the simulation model supports the relationship between the supplier and the original equipment manufacturer in the automotive industry. We demonstrate and validate our work by means of a power window case study.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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