Timed test cases generation based on state characterization technique
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
Real time reactive systems interact with their environment, using inputs and outputs, within specified time constraints. For such systems, a functional misbehavior or a deviation from the specified time constraints may have catastrophic consequences. Therefore, ensuring the correctness of real time systems becomes very important. We introduce the potential faults which can be encountered in a timed system implementation. We adapt an existing test cases generation technique, based on state characterization set, to generate timed test cases from a timed system specification. We model a timed system with a Timed Input Output Automaton (TIOA), which is a variant of the Alur and Dill model (R. Alur and D. Dill, 1994). In order to generate the timed test suite, the TIOA is first transformed into a Nondeterministic Timed Finite State Machine (NTFSM) with a given granularity. We illustrate our method with an example.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it