Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Modèles de fiabilité logicielle× | Métriques de complexité logicielle× | |
|---|---|---|
| Domaine | Génie logiciel | Génie logiciel |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1979 | 1976 |
| Auteur d'origine≠ | Alok Goel and Kazuhira Okumoto | Thomas J. McCabe |
| Type≠ | stochastic model | quantitative measurement |
| Source fondatrice≠ | Goel, A. L., & Okumoto, K. (1979). Time-dependent error-detection rate model for software reliability and other performance measures. IEEE Transactions on Reliability, 28(3), 206–211. DOI ↗ | McCabe, T. J. (1976). A complexity measure. IEEE Transactions on Software Engineering, 2(4), 308–320. DOI ↗ |
| Alias≠ | reliability growth model, failure rate prediction, SRGM | code complexity analysis, complexity measurement |
| Apparentées | 4 | 4 |
| Résumé≠ | Software reliability models predict the behavior of failure rates during testing and operation, estimating when software achieves required reliability targets. Introduced by Goel and Okumoto (1979), these stochastic models capture how defect discovery declines as testing progresses. Organizations use reliability models to forecast release readiness, estimate testing duration, and validate quality achievement. | Software complexity metrics quantify the structural and operational difficulty of code through numerical measurements. Introduced by Thomas McCabe in 1976, cyclomatic complexity became the foundational approach. These metrics assess maintainability, testability, and defect risk, enabling teams to identify problematic code regions and guide refactoring efforts. |
| ScholarGateJeu de données ↗ |
|
|