Building a Game Engine: A Tale of Modern Model-Driven Engineering
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
Game engines enable developers to reuse assets from previously developed games, thus easing the software-engineering challenges around the video-game development experience and making the implementation of games less expensive, less technologically brittle, and more efficient. However, the construction of game engines is challenging in itself, it involves the specification of well defined architectures and typical game play behaviors, flexible enough to enable game designers to implement their vision, while, at the same time, simplifying the implementation through asset and code reuse. In this paper we present a set of lessons learned through the design and construction PhyDSL-2, a game engine for 2D physics-based games. Our experience involves the active use of modern model-driven engineering technologies, to overcome the complexity of the engine design and to systematize its maintenance and evolution.
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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 | 0.001 | 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