IMMoS: a methodology for integrated measurement, modelling and simulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract One reason for the relatively small number of real‐world applications of simulation in software engineering is the existing lack of guidance in creating and formulating the related models and in the isolated usage of associated techniques. In order to support both strategic and project management in software organizations, a methodology for integrated measurement, modelling and simulation (IMMoS) was developed and validated. The hybrid approach integrates the individual strengths of its inherent methodological elements and concepts. The core element of IMMoS is the simulation modelling method system dynamics (SD), which integrates quantitative dynamic models with quantitative and qualitative static models in a natural way. The novelty of IMMoS is twofold. First, it enhances existing guidance for SD modelling by adding a component that enforces goal‐orientation, and by providing a refined process model with detailed description of activities, entry/exit criteria, input/output products, and roles involved. Secondly, it describes how to combine SD modelling with goal‐oriented measurement and descriptive process modelling, thus improving efficiency and smoothly closing the gap to established methods in empirical software engineering. IMMoS has been initially evaluated. The effectiveness and efficiency of IMMoS is supported with empirical evidence from two industrial case studies and one controlled experiment. Copyright © 2003 John Wiley & Sons, Ltd.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it