On the syllogistic structure of object-oriented programming
Bibliographic record
Abstract
Recent works by J.F. Sowa (2000) and D. Rayside and G.T. Campbell (2000) demonstrate that there is a strong connection between object-oriented programming and the logical formalism of the syllogism, first set down by Aristotle in the Prior Analytics (1928). In this paper, we develop an understanding of polymorphic method invocations in terms of the syllogism, and apply this understanding to the design of a novel editor for object-oriented programs. This editor is able to display a polymorphic call graph, which is a substantially more difficult problem than displaying a non-polymorphic call graph. We also explore the design space of program analyses related to the syllogism, and find that this space includes Unique Name, Class Hierarchy Analysis, Class Hierarchy Slicing, Class Hierarchy Specialization, and Rapid Type Analysis.
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How this classification was reachedexpand
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".