CORBA views: distributing objects with views
Bibliographic record
Abstract
We propose a model for building object oriented applications based on the composition of application slices or fragments that provide their own overlapping definitions or expectations of the same domain objects. Different slices may implement different functional or implementation concerns, or embody different access rights and privileges to the same domain objects. We call such slices views and we recognize that the behavior embodied in views may be abstracted into generic class-like algebraic structures called viewpoints, from which views for specific domain classes may be generated. We are interested in the problem of distributing view based applications when different sites access different slices of the same domain objects. Specifically, we are interested in the problem of offering different views of the same domain objects to different client programs in a CORBA-like environment. We first discuss the principles behind view programming, and then explore ways in which objects with views may be distributed in a way that support's different sets of functionalities to different client programs. An interesting application of view programming in a distributed context is the selective duplication of object slices.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".