The Software Engineering Body of Knowledge: A Benchmarking Tool for Organizational Process Assessment and Improvement – Case Study
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 Guide to the Software Engineering Body of Knowledge (the SWEBOK Guide) represents the consensus on the knowledge that software engineers, and their organizations, should use whenever and wherever appropriate in software development. This paper presents an innovative use of this SWEBOK Guide as a benchmarking reference for software organizations interested in process improvement and looking for best practices. Process improvement approaches help organizations improve their processes and their performance. Before implementing improvements to existing processes, it is necessary to benchmark organization’s practices already in place against a reference, identifying process weaknesses and looking for best practices that can contribute to process improvement according to corporate priorities. This paper presents two industry case studies illustrating the use of the SWEBOK Guide for benchmarking purposes and process improvements. This paper presents also quantitative results of productivity and quality analyses in both organizations and discusses the candidate linkages. Keywords: Appraisal, Best Practices, Process Improvement, SWEBOK
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it