Aspect-oriented requirements engineering for software product lines
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
Requirements engineering (RE) helps to identify, analyze and document system requirements. Proper analysis and understanding of system requirements is important because it helps to discover any requirements defects or mistakes in the early stages of development. Several processes and techniques have been developed to assist requirements engineering activities for product development. However, most of the existing product line practices do not comprise all the RE activities required for proper identification, analysis and understanding of product line requirements. In this paper, we propose a systematic and iterative RE approach for product line development. The approach includes all the activities required for proper identification, analysis, modeling and specification of product line requirements. In addition to this, it proposes several specific techniques such as aspect-orientation or separation of concerns, product maps and extensible markup language (XML) to assist different RE activities. The concept of aspect-oriented programming is used for analyzing the common and variable requirements. Product maps are used for determining the scope and characteristics of the product family. Extensible markup language (XML) is used for requirements specification and traceability.
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 | 0.003 |
| 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 | 0.001 |
| 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