The Development of International Standards to Facilitate Process Improvements for Very Small Entities
Bibliographic record
Abstract
Industry recognizes that Very Small Entities (VSEs) that develop software are very important to the economy. A Very Small Entity (VSE) is an entity (enterprise, organization, department or project) with up to 25 people..Failure to deliver a quality product on time and within budget threatens the competitiveness of VSEs and impacts their customers. One way to mitigate these risks is to put in place proven software engineering practices. Many international standards and models, like ISO/IEC 12207 or CMMI®1, have been developed to capture proven engineering practices. However, these documents were not designed for VSEs and are often difficult to apply in such settings. This chapter presents a description of the development of process improvement international standards (IS) targeting VSEs developing or maintaining software as a standalone product or software as a component of a system. The documents used by ISO/IEC JTC1/SC72 Working Group 24 (WG24), mandated to develop a set of standards and guides, and the approach that led to the development, balloting of the ISs, and TRs (Technical Reports) for VSEs are also presented. The chapter focuses on the ISO/IEC 29110 Standard3, the development of means to help VSEs improve their processes, and the description of a few pilot projects conducted to implement the processes of ISO/IEC 29110 standard.
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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 | 0.000 |
| 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 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".