Implementation and Verification of Implicit-Invocation Systems Using Source Transformation
Why this work is in the frame
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Bibliographic record
Abstract
In this paper we present a source transformation-based framework to support uniform testing and model checking of implicit-invocation software systems. The framework includes a new domain-specific programming language, the Implicit-Invocation Language (IIL), explicitly designed for directly expressing implicit-invocation software systems, and a set of formal rule-based source transformation tools that allow automatic generation of both executable and formal verification artifacts. We provide details of these transformation tools, evaluate the framework in practice, and discuss the benefits of formal automatic transformation in this context. Our approach is designed not only to advance the state-of-the-art in validating implicit-invocation systems, but also to further explore the use of automated source transformation as a uniform vehicle to assist in the implementation, validation and verification of programming languages and software systems in general.
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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 | 0.001 |
| 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