On Problems in Polymorphic Object-Oriented Languages With Self Types and Matching
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Bibliographic record
Abstract
Subtyping is a basic concept in object-oriented languages. It supports subsumption but, unfortunately, it does not support inheritance of binary methods, i.e., methods taking another argument of type Self? – the same type as the object itself. For this reason, a relation, called matching, on recursive object types has been proposed. This relation does not support subsumption but it allows to inherit binary methods. Two different definitions of matching, called F-bounded and higher-order subtyping, have been proposed and discussed. It was shown that the higher-order interpretation has better theoretical properties, i.e., it leads to a reflexive and transitive matching relation. In this paper we concentrate on two problems in languages with self types and matching based on the higher-order interpretation. We show that the flexibility of self types may not allow the programmer to define certain classes and/or methods which are based on constant values. Furthermore, the higher-order interpretation, especially in the context of bounded quantification, is too restrictive. We argue that a language should be based on both versions of matching and a notion of a type This distinguished from the type Self.
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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 | 0.001 |
| 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