Context independent unique sequences generation for protocol testing
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
A number of test sequence generation methods proposed for protocols represented as extended finite state machines (EFSMs) use state identification sequences for checking the states. However, neither a formal definition nor a method of computation of these sequences for an EFSM state is known. We define a new type of state identification sequence, called context independent unique sequence (CIUS) and present an algorithm for computing it. A unified method based on CIUSes is developed for automatically generating executable test cases for both control flow and data flow aspects of an EFSM. In control flow testing, CIUSes are very useful in confirming the tail state of the transitions. In data flow testing, CIUSes improve the observability of the test cases for the def-use associations of different variables used in the EFSM. Unlike general state identification sequences, the use of CIUSes does not increase the complexity of the already intractable feasibility problem in the test case generation.
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 | 0.001 |
| 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