Enabling Software Evolution Via AOP and Reflection Report on the Workshop RAM-SE at ECOOP 2007
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. Following last three years ’ RAM-SE (Reflection, AOP and Meta-Data for Software Evolution) workshop at the ECOOP conference, the RAM-SE’07 workshop was a successful and popular event. As its name implies, the workshop’s focus was on the application of reflective, aspect-oriented and data-mining techniques to the broad field of software evolution. Topics and discussions at the workshop included mechanisms for supporting software evolution, technological limits for software evolution and tools and middleware for software evolution. The workshop’s main goal was to bring together researchers working in the field of software evolution with a particular interest in reflection, aspect-oriented programming and meta-data. The workshop was organized as a full day meeting, partly devoted to presentation of submitted position papers and partly devoted to panel discussions about the presented topics and other interesting issues in the field. In this way, the workshop allowed participants to get acquainted with each other’s work, and stimulated
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 | 0.001 | 0.002 |
| 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 | 0.000 | 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