Proceedings of the 16th International ACM Sigsoft symposium on Component-based software engineering
Bibliographic record
Abstract
Welcome to the 16th International ACM Sigsoft Symposium on Component-Based Software Engineering -- CBSE 2013! Since its early editions, CBSE has emerged as a flagship research event for the component community. It encompasses research (both theoretical and applied) that extends the state-of-the-art in component specification, composition and reuse, analysis, testing, and verification. Past themes for CBSE include for Long-Lived (2012), for Dynamic Environments (2011), beyond Reuse (2010), and for Large-Scale Systems of Systems and Ultra-Large (2009). The general theme of CBSE 2013 is in the wild: from cyber-physical systems to the cloud!. The call for papers attracted 43 submissions from Europe (Italy, Sweden, Germany, France, Czech Republic, United Kingdom), Asia (Saudi Arabia, Iran, Thailand, China, Japan, India), America (Canada, United States, Brazil), and Australia. Each paper received three reviews. The Program Committee, after extensive discussions, decided to accept 20 papers (16 regular papers and 4 short papers) that cover a variety of topics, including Adaptable Components, Component Verification, Component Composition and Reuse, Component Design, Component Analysis, and Component Quality Assurance. We hope that the CBSE 2013 proceedings will serve as reference literature for academic researchers and practitioners working in the area of Component-Based Software Engineering. CBSE 2013 is part of the federated event CompArch 2013 together with QoSA 2013: 9th International ACM SIGSOFT Conference on the Quality of Software Architectures, ISARCS 2013: 4th International ACM SIGSOFT Symposium on Architecting Critical Systems, and WCOP 2013: 18th International Doctoral Symposium on Components and Architecture. We thank the CompArch general chair Philippe Kruchten and the CompArch organization team for coordinating and setting up the various events.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.075 | 0.038 |
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".