Towards Web Collaborative Modelling for the User Requirements Notation Using Eclipse Che and Theia IDE
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
Collaborative modelling has become a necessity when developing a complex system or in a team of modellers with a diverse set of expertise. Textual notations have a long history in software engineering because of their fast editing style, simple usage, and scalability. Therefore, we propose a novel collaborative modelling framework for the graphical User Requirements Notation (URN) which we call tColab. It uses the text-based TGRL (Textual Goal-oriented Requirement Language) to build URN goal models and then automatically generates corresponding graphical models. This framework is based on the architecture of Eclipse Che and Theia. On one side, Theia provides support for LSP (Language Server Protocol) so that textual models can be built and their corresponding graphical models can be generated in a browser IDE (Integrated Development Environment). On the other hand, Eclipse Che adds support for collaboration where multiple modellers can contribute to building the textual models in an online collaborative manner. This initiative aims to replace the jUCMNAV tool, which is the most comprehensive URN modelling tool to date but only supports a single user.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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