Proceedings of the ACM SIGPLAN 2002 conference on Programming language design and implementation
Bibliographic record
Abstract
The program committee is pleased to present this proceedings of the 2002 ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2002). PLDI 2002 was held June 17--19, 2002, in Berlin, Germany, marking the first time that the conference has been held in Europe.The PLDI conference series is one of the premier forums for the presentation of new and exciting research in the areas of programming language design and implementation. Traditionally, it attracts a wide audience including researchers, practitioners, students and educators.This year the program committee selected 28 papers from 169 papers that were submitted. Each paper was rigorously reviewed by three members of the program committee and in many cases an external expert provided additional feedback. As is always the case with PLDI, many very good papers could not be accepted, and we hope that these will appear in other forums.In addition to the presentation of the 28 selected papers, PLDI 2002 also featured two invited presentations by the 2001 and 2002 winners of the ACM SIGPLAN Programming Languages Achievement Award. The 2001 winner was Professor Robin Milner, University of Cambridge, UK, and the 2002 winner was announced at the conference.This year, the program committee was slightly larger than in the past, and consisted of 19 members, including Jens Knoop who was also the PLDI 2002 general chair. As was the case for PLDI 2001, we asked for full papers to be submitted and each committee member reviewed about 28 such submissions. Following SIGPLAN policy, committee members were not allowed to submit papers to the conference.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.110 | 0.057 |
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 source (direct Gemma or distilled Codex), 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".