A Formal Approach to the Verification of Adaptability Properties for Mobile Multimodal User Interfaces
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
Multimodal User Interfaces (MUIs) offer to users the possibility to interact with systems using one or more modalities. In the context of mobile systems, this will increase the flexibility of interaction and will give the choice to use the most appropriate modality. These interfaces must satisfy usability properties to guarantee that users do not reject them. Within this context, we show the benefits of using formal methods for the specification and verification of multimodal user interfaces (MUIs) for mobile systems. We focus on the usability properties and specifically on the adaptability property. We show how transition systems can be used to model the MUI and temporal logics to specify usability properties. The verification is performed by using fully automatic model-checking technique. This technique allows the verification at earlier stages of the development life cycle which decreases the high costs involved by the maintenance of such systems.
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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 | 0.001 | 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 | 0.002 | 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