Comparing methodologies for the transition between software requirements and architectures
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
The transition from software requirements to software architectures has consistently been one of the main challenges during software development. Various methodologies that aim at helping with this transition have been proposed. However, no systematic approach for assessing such methodologies exists. Also, there is little consensus on the technical and non-technical issues that a transition methodology should address. Hence, we present a method for assessing and comparing methodologies for the transition from requirements to architectures. This method also helps validate newly proposed transition methodologies. The objective of such validations is to assess whether or not a methodology has the potential to lead to better architectures. For that reason, this paper discusses a set of commonly known but previously only informally described criteria for transition methodologies and organizes them into a schema. In the paper we also use our method to characterize a set of 14 current transition methodologies. This is done to illustrate the usefulness of our approach for comparing transition methodologies as well as for validating newly proposed methodologies. Characterizing these 14 methodologies also gives an overview of current transition methodologies and research.
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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 | 0.001 |
| 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 | 0.000 |
| 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