Automatic synthesis of multi-tasking implementations from real-time object-oriented models
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
Presents an approach towards the automatic synthesis of implementations from real-time object-oriented design models. From an application design model that addresses the functional requirements of the system, and given end-to-end timing requirements, our synthesis approach generates a feasible implementation model, i.e. one that will meet the timing requirements. The synthesis process is supported by automatic code generation that can take the application design model and the synthesized implementation model, and can generate code for the target platform. The synthesis of an implementation model is facilitated through the use of a generic (application-independent) implementation architecture, thereby reducing the synthesis problem to selecting a mapping of the application design model to the artifacts of the implementation architecture. In this paper, we use a multi-threaded event handling architecture with fixed event priorities. The synthesis problem then consists of determining priorities for events and mapping events to threads. We show how, given such a mapping, the response times can be analyzed, and then how, using the analysis, a feasible implementation model can be automatically synthesized.
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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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