Checklist-based Software Quality Evaluation of Tango Controls
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
Tango Controls is an open-source framework for distributed control systems used by a growing number of industrial and institutional partners. Despite the many benefits it provides to users, such as a growing community, industrial support, highly scalable, and so on, there are some disadvantages to this trending framework. Uncovering these drawbacks creates users’ awareness while considering using this open-source software in their control systems and motivates the Tango Controls development community to fix these issues. In this study, first, we review the research conducted to evaluate, optimize and compare Tango Controls with other trending commercial and open-source control system frameworks. Afterwards, we evaluate Tango Controls via a checklist-based approach by considering two types of control systems and scrutinizing the frameworks’ documentation. As a result, we detect reliability and security drawbacks that have not been identified in relevant studies as the first step of our future work to optimize Tango Controls by introducing a toolset.
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 | 0.004 | 0.005 |
| 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 | 0.000 | 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