Vector-based method for measuring and comparing software requirements implementation
Bibliographic record
Abstract
This paper presents the results of measuring the completeness of software requirements implementation and of comparing multiple software products based on the same requirements specification, by using an original approach settled on a vector-based method. The application of this method is presented in a practical way, by analyzing 6 software products using two different development processes: UPEDU - a scaled-down version of the organized process RUP and XP - a member of the agile methodologies. An experts' committee measured and analyzed the realization quality of each of 109 requirements of equal importance and judged them based on an evaluation vector system. Two groups of requirements were identified referring dynamic functions and static functions of the system. The observational study was conducted in an academic environment.An important contribution of this paper is the vector-based comparison method that could be generalized and applied in any other setting. The findings of this empirical study point to a potential link that may exist between the quality of the implemented requirements and the process used by the development teams.
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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 | 0.001 | 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 | 0.001 |
| 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 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".