Findings from Phase 2 of the SPICE trials
Bibliographic record
Abstract
Abstract The international SPICE (Software Process Improvement and Capability dEtermination) project was set up to support the development of the ISO/IEC 15504 standard for software process assessment (SPA). The project mounted a set of trials to validate the emerging standard against the goals and requirements defined at the start of the SPICE project and to verify the consistency and usability of its component parts. A considerable number of empirical evaluation studies have been conducted during the Phase 2 SPICE Trials based on ISO/IEC PDTR 15504 (between September 1996 and June 1998). Such an exercise is unprecedented in the software engineering standards community and it provides a unique opportunity for empirical validation. The purpose of this paper is to present major parts of the findings of the empirical studies conducted as part of the SPICE Project during Phase 2 of the SPICE Trials. The topics covered in this paper include (i) investigation into reasons for performing SPAs, (ii) evaluation of the internal consistency of the capability dimension, (iii) use of interrater agreement as a measure of the reliability of assessments, (iv) evaluation of the predictive validity of process capability, (v) evaluation of an exemplar model (Part 5), (vi) identification of factors influencing assessor effort, and (vii) empirical comparison between ISO/IEC PDTR 15504 and ISO 9001. Major lessons learned as well as future research directions are summarized on the strengths and weaknesses of ISO/IEC 15505. Copyright © 2001 John Wiley & Sons, Ltd.
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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 | 0.160 | 0.475 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".