Object-oriented real-time concurrency
Bibliographic record
Abstract
The primary goal of a real-time system is predictability. Achieving this goal requires all levels of the system to work in concert to provide fixed worst-case execution-times. Un-fortunately, many real-time systems are overly restrictive, providing only ad-hoc scheduling facilities and basic concurrent functionality. Ad-hoc scheduling makes developing, verifying, and maintaining a real-time system extremely difficult and time consuming. Basic concurrent functionality forces programmers to develop complex concurrent programs without the aid of high-level concurrency features.Encouraging the use of sophisticated real-time theory and methodology, in conjunction with high-level concurrency features, requires flexibility and extensibility. Giving real-time programmers access to the underlying system data-structures makes it possible to interact with the system to incorporate new ideas and fine-tune specific applications. This paper explores this approach by examining its effect on a selection of crucial real-time issues: real-time monitors, timeouts, dynamic-priority scheduling and basic priority inheritance. The approach is implemented in μC++.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".