Bridging concrete and abstract syntaxes in model‐driven engineering: a case of rule languages
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
Abstract The paper covers the problem of bridging the gap between abstract and textual concrete syntaxes of software languages in the model‐driven engineering (MDE) context. This problem has been well studied in the context of programming languages, but due to the obvious difference in the definitions of abstract syntax, MDE requires a new set of engineering principles. We first explore different approaches to defining abstract and concrete syntaxes in the MDE context. Next, we investigate the current state of languages and techniques used for bridging between textual concrete and abstract syntaxes in the context of MDE. Finally, we report on lessons learned in experimenting with the current technologies. In order to provide a comprehensive coverage of the problem under study, we have selected a case of Web rule languages. Web rule languages leverage various types of syntax specification languages; and they are complex in nature and large in terms of the language elements. Thus, they provide us with a realistic analysis framework based on which we can draw general conclusions. Based on the series of experiments that we conducted with the analyzed languages, we propose a method for approaching such problems and report on the empirical results obtained from the data collected during our experiments. Copyright © 2009 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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