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| Analyse des points de fonction× | Métriques de complexité logicielle× | |
|---|---|---|
| Domaine | Génie logiciel | Génie logiciel |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1979 | 1976 |
| Auteur d'origine≠ | Allan Albrecht | Thomas J. McCabe |
| Type | quantitative measurement | quantitative measurement |
| Source fondatrice≠ | Albrecht, A. J. (1979). Measuring application development productivity. In Proceedings of the IBM Applications Development Symposium (pp. 83–92). link ↗ | McCabe, T. J. (1976). A complexity measure. IEEE Transactions on Software Engineering, 2(4), 308–320. DOI ↗ |
| Alias≠ | FPA, function points, IFPUG sizing | code complexity analysis, complexity measurement |
| Apparentées | 4 | 4 |
| Résumé≠ | Function point analysis (FPA) quantifies software size by counting business functions and user interactions independent of technology or programming language. Introduced by Albrecht (1979), FPA measures delivered functionality, enabling effort estimation, productivity benchmarking, and software value assessment. Organizations use FPA for project contracts, vendor comparison, and portfolio management. | 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. |
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