Model transformation of dependability-focused requirements models
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
Recent research has focused on extending standard requirements elicitation processes to address potential abnormal situations that can interrupt normal system interaction at run-time. We proposed a process, DREP, that extends use case-driven modelling with elements that allow the modelling of system behaviour in exceptional situations. This paper discusses the challenge of using the notions of exceptional behaviour and outcomes defined in use cases within a MDE process. In order to create a more formal specification model with activity diagrams, the use cases have to be well-formed to begin with. We describe precise transformation rules to systematically create an activity diagram corresponding to each use case. Special stereotypes are introduced to document partial or degraded outcomes and handling activities. The model resulting from the transformation unambiguously specifies the system interactions required to satisfy the user, as well as exceptional interactions that can lead to degraded service provision.
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 | 0.001 |
| 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