Proceedings of the joint international and annual ERCIM workshops on Principles of software evolution (IWPSE) and software evolution (Evol) workshops
Bibliographic record
Abstract
IWPSE-Evol'09 merges the International Workshop on Principles of Software Evolution (IWPSE) and the annual ERCIM Workshop on Software Evolution (Evol), and is the premier event dedicated to software evolution in 2009. To celebrate the 10th anniversary of IWPSE, the 5th anniversary of the ERCIM evolution workshop, and the 20th anniversary of ERCIM itself, we have chosen to join forces by organising a common event at ESEC/FSE 2009, under the special theme "The Future of Software Evolution". We explicitly solicited submissions that take a historical perspective on a particular facet of software evolution research, practice or education, argue for the current challenges, and speculate on what the future might bring. We received 36 submissions, 20 of which were full papers. The short papers comprised 14 position papers and 2 tool papers. We asked authors to classify their submissions according to 15 topics, in order to facilitate matching with the expertise of the program committee members. Every paper could be classified in more than one topic. To give an idea of current research in software evolution, we list the six most popular topics: Processes, paradigms and methodologies for software evolution (14 papers)Measuring, analysing and visualising evolution (11 papers)Empirical studies and experience reports (10 papers)Consistency management and impact analysis (7 papers)History and future of software evolution (the workshop's theme); applying software evolution (each topic with 6 papers) After peer review and discussion of the submitted papers by an international program committee of experts in the field, only 10 full papers and 8 short papers were accepted. As can be seen from the table of contents of these proceedings, the accepted papers cover a very wide range of issues, from specific techniques to cope with software evolution to infrastructure that facilitates research in this field, and approaches, from formal to empirical. We hope that these proceedings will serve as a valuable reference for future software evolution researchers and for developers facing the problems of ever-changing software systems. Given the historical perspective of this year's edition of the joint workshop, the program chairs invited Takuya Katayama (Professor at the Japan Advanced Institute of Science and Technology), the founding father of the IWPSE workshop series, and Tom Mens (Professor at the University of Mons, Belgium), the chair and founding father of the ERCIM Working Group on Software Evolution, to give anniversary talks on IWPSE and EVOL, respectively. They accepted the challenge to look back on the history of IWPSE and the ERCIM Working Group, and to highlight future opportunities for software evolution research. We are also delighted that Hausi Müller (Professor at the University of Victoria, Canada) accepted our invitation to give a keynote talk on a particular field of software evolution that has seen quite some activity in recent years: run-time evolution to enable autonomic systems that self-adapt to changing environments.
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.097 | 0.039 |
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".