On queued testing and its application to delay-insensitive systems
Bibliographic record
Abstract
The thesis elaborates a so-called queued testing framework for input/output transition systems (IOTS) and demonstrates its applicability to delay-insensitive (DI) systems. IOTS are an appropriate model of systems with concurrent input and output, such as distributed systems and asynchronous circuits. We develop the queued testing framework based on the assumption that output of IOTS cannot be blocked. For this, a tester is separated into two independent processes: one applies stimuli and the other observes responses of a system under test through finite queues. We apply queued testing to DI systems, concurrent systems that are invariant under communication delays. As we prove, however, most DI systems are not robust, which means that not all input actions are acceptable (specified) in each state. The theorem is proved for a unified formalization of DI systems that considers a wide range of delay models: single-capacity buffers, queues, stacks, etc. To test DI systems, we extend the queued testing framework, which is originally elaborated for fully specified IOTS, to cover partially specified IOTS by preventing testers from sending unspecified input actions. Case studies in the thesis demonstrate that the extended queued testing framework is applicable to DI systems.
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.
How this classification was reachedexpand
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".