Reliability estimation of hierarchical software systems
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
The reliability evaluation of hardware systems is usually well integrated into the design process. Because it is done early, this reliability evaluation is useful in making design decisions. Software Reliability Evaluation (SRE), on the other hand, has been mostly conducted after development has been completed, therefore offering little or no input into the design. This paper proposes a simple approach to estimate the reliability of software systems that are composed of a hierarchy of modules. Furthermore, the proposed approach takes advantage of the familiar reliability block diagram (RBD) methodology, which has long been used for hardware reliability estimation. This paper demonstrates how RBD can be used to represent hierarchical software systems. Using this technique early in the development process can offer system designers the opportunity to conduct sensitivity analysis that combines both hardware and software components. Criticality is also shown to be useful in the proposed SRE approach. Examples are given to show how criticality makes the SRE more realistic than the use of RBD alone.
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 | 0.003 |
| 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