Specification of abstract data types using real-time process algebra (RTFA)
Bibliographic record
Abstract
The real-time process algebra (RTFA) provides a new approach to the specification and refinement of real-time systems. This paper presents a study on the specification of a set of abstract data types (ADTs) by using RTPA. The objectives of this work are to demonstrate the expressiveness of the RTPA notations and specification method, and to build a fundamental ADT library for RTPA by recursively applying the RTPA notations. Eleven ADTs, such as stack, record, array, queue, sequence, list, etc., have been selected and specified in RTPA. An ADT, Queue, is adopted in this paper to shown the RTPA specification and refinement methods. The queue specification in RTPA is contrasted to a conventional logic-based specification, and the features and advantages of the RTPA notation system is demonstrated. This case study shows that with RTPA, ADTs can be described and specified not only as static data types, but also dynamic real-time components, which enables ADTs to be applied in the real-time environment as predefined or embedded special architectural components.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".