Proceedings of the 5th international conference on Generative programming and component engineering
Bibliographic record
Abstract
It is our great pleasure to welcome you to GPCE'06, a premier forum for presenting and discussing research results and industry strength technologies in areas of generative programming and component engineering. Generative programming brings unique, useful engineering qualities that are missing in conventional programming approaches-especially when designing generic, adaptable and maintainable software. Generative programming is one of the few emerging technologies that can bridge the gap between software architecture and code.GPCE has traditionally brought together researchers and practitioners interested in a wide array of issues related to automation of software development, better control over software complexity, and improvement of programmer productivity in general. GPCE has been also an environment for cross-fertilization between the programming language and software engineering research communities. It was our intention to continue these major GPCE threads and traditions. This year's GPCE is co-located with OOPSLA, which will ensure the fusion of ideas pertinent to software development, both theory and practice.We received 85 papers from around the world. Many papers were of very high quality, as evidenced by the strength of the GPCE'06 technical program. The program committee accepted 30 papers covering a wide spectrum of topics. The tutorial program presenting industry strength technologies shows the maturity of generative programming, and is targeted at practitioners as well as researchers. Paper presentations, complemented by seven tutorials, four workshops, and two keynotes, form a conference program that we hope all participants will find exciting and worth attending.
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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 | 0.000 | 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 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".