The Evolution of the ISO/IEC 29110 Set of Standards and Guides
Bibliographic record
Abstract
While the quality of products is a competitive advantage for very small software development organizations, the usage of Software and Systems Engineering standards amongst such very small organizations is extremely low. A key factor in the literature explaining this lack of quality standards adoption is the perception by small and very small organizations that such standards have been developed for large multi-national companies and not with small and very small organizations in mind. The ISO/IEC 29110 standard is unique amongst software and systems engineering standards, in that the working group (ISO/IEC JTC1/SC7 WG 24) mandated to develop a new standard approached industry to conduct a needs assessment and gather actual requirements for a new standard as part of the standards development process. This paper presents a historical perspective behind the development of the ISO/IEC 29110 systems and software engineering standard and its constituent components, including the rationale behind its development and the innovative design of implementation guides to assist very small companies in adopting the standards. Further this paper will present an overview of the various parts of the ISO/IEC 29110 family and briefly present the plans for the future evolution of this series of standards.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".