Proceedings of the 4th international workshop on Software and performance
Bibliographic record
Abstract
The study of software performance is critical for the ongoing development of software systems. Despite its increasingly central role in the software engineering, many basic questions about software performance remain unanswered. While much progress has been made, the field still seeks better models, methods and integrated tools for performance engineering that can be easily used by software developers. New challenges are posed by society and industry in terms of QoS-aware software architectures and components. The Workshop on Software and Performance serves to bring together researchers and industry professionals attacking these challenging problems faced by the software and performance community. This is the fourth WOSP. Previous workshops were held in Santa Fe, Ottawa, and Rome. The conference is now regularly scheduled on an 18 month cycle.The workshop program is structured along six main themes: 1) software performance tools and techniques, 2) performance analysis, 3) performance measurement and modeling, 4) software and performance engineering, 5) quality of service, and 6) performance driven software design methods. We are confident that the body of knowledge selected by the WOSP Committee will contribute to advance the state of the art of the field.The WOSP'04 program is the result of a selective review process. The program committee received 70 submissions; from these 18 were accepted as full papers and 20 were accepted as posters. The program committee meeting was held electronically using Cyberchair. Most reviews were provided by program committee members; in some cases outside experts were also consulted.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.071 | 0.031 |
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".