Type-Driven Gradual Security with References
Why this work is in the frame
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Bibliographic record
Abstract
In security-typed programming languages, types statically enforce noninterference between potentially conspiring values, such as the arguments and results of functions. But to adopt static security types, like other advanced type disciplines, programmers face a steep wholesale transition, often forcing them to refactor working code just to satisfy their type checker. To provide a gentler path to security typing that supports safe and stylish but hard-to-verify programming idioms, researchers have designed languages that blend static and dynamic checking of security types. Unfortunately, most of the resulting languages only support static, type-based reasoning about noninterference if a program is entirely statically secured. This limitation substantially weakens the benefits that dynamic enforcement brings to static security typing. Additionally, current proposals are focused on languages with explicit casts and therefore do not fulfill the vision of gradual typing, according to which the boundaries between static and dynamic checking only arise from the (im)precision of type annotations and are transparently mediated by implicit checks. In this article, we present GSL Ref , a gradual security-typed higher-order language with references. As a gradual language, GSL Ref supports the range of static-to-dynamic security checking exclusively driven by type annotations, without resorting to explicit casts. Additionally, GSL Ref lets programmers use types to reason statically about termination-insensitive noninterference in all programs, even those that enforce security dynamically. We prove that GSL Ref satisfies all but one of Siek et al.’s criteria for gradually-typed languages, which ensure that programs can seamlessly transition between simple typing and security typing. A notable exception regards the dynamic gradual guarantee, which some specific programs must violate if they are to satisfy noninterference; it remains an open question whether such a language could fully satisfy the dynamic gradual guarantee. To realize this design, we were led to draw a sharp distinction between syntactic type safety and semantic type soundness , each of which constrains the design of the gradual language.
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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 | 0.000 | 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 | 0.000 |
| 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