An Amalgamated Dynamic and Static Architecture Reconstruction Framework to Control Component Interactions 259
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
View-based software development is well adopted in for techniques still consider a single view of a software system with restricted scope of analysis. In this paper, we propose a novel approach that amalgamates dynamic and static views of a software system. The dynamic view is represented through profiling information that is extracted from executing a set of task scenarios that cover frequently used software features. The obtained profiling information is then embedded into a static view recovery process. We propose a pattern based structure recovery, as static view, that defines the high-level architecture of the software system using abstract components and interconnections that is defined using an architecture query language (AQL). In this context, both static and dynamic aspects of the software system are used to collect software entities into cohesive components whose dynamic interactions can be controlled. The whole recovery process is modeled as a valued constraint satisfaction problem (VCSP). A case study with promising results on the Xfig drawing tool has also been presented.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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