Proceedings of the Sixteenth International Workshop on the ACL2 Theorem Prover and its Applications
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
It is common practice during Instruction Set Architecture (ISA) development to create an ISA simulator, usually in C/C++.We describe an experiment in which we implement such an ISA simulator for a derivative of a popular ISA written in a subset of Algorithmic C, to allow for the verification of binary programs targeting that ISA, as well as to aid in the validation of the ISA model via simulated execution of test programs on the model.Algorithmic C defines C++ header files that enable compilation to both hardware and software platforms, providing support for the peculiar bit widths employed, for example, in floating-point hardware design.We utilize a toolchain, due to Russinoff and O'Leary, that provides a translation from a restricted subset of Algorithmic C to the Common Lisp subset supported by the ACL2 theorem prover.This toolchain, called RAC, is documented in Russinoff's recent book on floating-point hardware verification.We create an ISA simulator in this C++ subset, use RAC to translate this simulator code to ACL2, produce small binary programs for the ISA that we use to validate the simulator, and utilize the ACL2 Codewalker decompilation-into-logic facility to prove those programs correct.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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