Proposal of the Assessment of the 4-Workflow Model for Secure Agile Process Practices
Bibliographic record
Abstract
In today’s fiercely competitive business landscape, organizations must operate with speed and foster innovation. Consequently, the majority of businesses have embraced an agile development approach. However, the heightened pace of development presents various vulnerabilities for exploitation by cybercriminals, particularly when the security of software lifecycle processes is neglected or deferred to reactionary methods after compromises take place. To address this challenge, the solution lies in advocating for a light-weight framework where security receives its essential needed attention from all aspects of the process: requirements and sprint, dependencies management, deployment process, and incident and response management. Therefore, we give a background on our 4-workflow solution, followed by a detailed survey on the recent multivocal literature on how to assess this solution in practice and we produced a resulting evaluation methodology and a taxonomy of tools and metrics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".