A Semi-Automated Tool for Requirements Trade-off Analysis.
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. In designing most systems, requirements analysts face many competing requirements, such as performance, usability, costs, and so forth. Ideally, analysts would like to quantitatively measure consequences of solutions on requirements and risks, and extract stakeholders ’ preferences in terms of numerical weights. However, during the early stages of requirements and system design, it is hard to quantitatively measure all factors on a similar scale and quantify stakeholders ’ preferences. This contribution proposes a semi-automated decision aid tool which allows the use of available but potentially incomplete quantitative and qualitative requirements and risk measures. It removed the need to elicit importance weights of requirements. Instead, stakeholders are asked how much they would relax the demand on one objective to better achieve another. The proposed tool extends the Even Swap method with formally defined rules for suggesting the next swap to decision stakeholders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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