Document driven certification of computational science and engineering software
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
This paper presents a documentation and development methodology to facilitate the certification of Computational Science and Engineering (CSE) software that is produced by professional end user developers to solve mathematical models of physical systems. To study the problems faced during quality assurance and certification activities, a case study was performed on legacy software used by a nuclear power generating company for safety analysis in a nuclear reactor. Although no errors were uncovered in the code, the documentation still needed significant updating for certification, since its was incomplete and inconsistent. During the case study, 27 issues were found with the documentation. This work proposes improvements to the case study software and other CSE software via a new template for the Software Requirements Specification (SRS) that clearly and sufficiently states the requirements, while satisfying the desired qualities for a good SRS. For developing the design and implementation, this paper suggests Literate Programming (LP) as an alternative to traditional structured programming. Literate Programming documents the numerical algorithms and the logic behind the development and the code together in the same document, the Literate Programmer's Manual (LPM). The LPM is developed in connection with the SRS. The explicit traceability between the theory, numerical algorithms and implementation (code), facilitates completeness and consistency, and simplifies the process of verification and the associated certification.
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 | 0.000 |
| 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