Towards a Meta-Model for Requirements-Driven Information for Internal Stakeholders
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
<strong>Abstract. [Context &amp; Motivation]</strong> Providing requirements-driven information (e.g., requirements volatility measures, requirements-design coverage information, requirements growth rates, etc.) falls within the realm of the requirements management process. The requirements engineer must derive and present the appropriate requirements information to the right internal stakeholders (IS) in the project. <strong>[Question / Problem]</strong> This process is made complex due to project-related factors such as numerous types of ISs, varying stakeholder concerns with regard to requirements, project sizes, a plethora of software artifacts, and many affected processes. However, there is little guidance in practice as to how these factors come into play together in providing the described information to the ISs. <strong>[Principle ideas/results]</strong> Based on analyzed data from an action research (AR) study we conducted in a large systems project in the rail-automation domain, we propose a meta-model that consists of the main entities and relationships involved in providing requirements-driven information to internal stakeholders within the context of a large systems project. The meta-model consists of five main entities and nine relationships that are further decomposed into three abstraction levels. We validated the meta-model in three phases by researchers and practitioners. &nbsp;[<strong>Benefits/Contribution]</strong> The meta-model is anticipated to facilitate: (i) control and management of process and resources for providing requirement-driven information to stakeholders and (ii) communication among internal stakeholders.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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