System performance requirements: A standards-based model for early identification, allocation to software functions and size measurement
Bibliographic record
Abstract
Background: In practice, the developers focus is on early identification of the functional requirements (FR) allocated to software, while the system non-functional requirements (NFRs) are left to be specified and detailed much later in the development lifecycle. Aim: A standards-based model of system performance NFRs for early identification and measurement of FR-related performance of software functions. Method: 1) Analysis of performance NFR in IEEE and ECSS standards and the modeling of the identified system/software performance functions using Softgoal Interdependency Graphs. 2) Application of the COSMIC-FSM method (e.g., ISO 19761) to measure the functional size of the performance requirements allocated to software functions. 3) Use of the COSMIC-SOA guideline to tailor this framework to service-oriented architecture (SOA) for performance requirements specification and measurement. 4) Illustration of the applicability of the proposed approach for specification and measurement of system performance NFR allocated to the software for an automated teller machine (ATM) in an SOA context. Results: A standards-based framework for identifying, specifying and measuring NFR system performance of software functions. Conclusion: Such a standards-based system performance reference framework at the function and service levels can be used early in the lifecycle by software developers to identify, specify and measure performance NFR.
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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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.002 |
| 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".