Specification and Verification of Communication Paradigms for CBSE in Event B
Bibliographic record
Abstract
The development of distributed computing systems and of their usage in domains such as the Internet of Things, Big Data, etc., raises numerous questions on the tools available to model the complexity of such systems. Non-formal modeling methods fail to create a rigorous way to describe and analyze these systems. In this paper, we propose an approach to model and analyze the structural and behavioural aspect of these systems using formal techniques. As a prerequisite, we build reusable model libraries to specify and verify communication paradigms for modeling software architectures of distributed systems in a component-based system engineering (CBSE) context. First, we describe high-level concepts for system architecture in a component-port-connector fashion as a metamodel. Then, we develop an Event-B interpretation of the metamodel adding communication characteristics such as buffering, FIFO and synchronicity. To validate our work, we studied the two well-known communication paradigms, namely message passing and remote procedure call.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".