Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Métricas de Complejidad del Software× | Análisis de cobertura de código× | |
|---|---|---|
| Campo | Ingeniería de software | Ingeniería de software |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1976 | 1988 |
| Autor original≠ | Thomas J. McCabe | Test Coverage Community |
| Tipo≠ | quantitative measurement | measurement and analysis |
| Fuente seminal≠ | McCabe, T. J. (1976). A complexity measure. IEEE Transactions on Software Engineering, 2(4), 308–320. DOI ↗ | Zhu, H., Hall, P. A. V., & May, J. H. R. (1997). Software unit test coverage and adequacy. ACM Computing Surveys, 29(4), 366–427. DOI ↗ |
| Alias≠ | code complexity analysis, complexity measurement | coverage metrics, test coverage, instrumentation-based measurement |
| Relacionados | 4 | 4 |
| Resumen≠ | 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. | Code coverage analysis measures the extent to which source code is executed by a test suite, quantifying which lines, branches, or paths are exercised. Tools instrument code to track execution, reporting coverage percentages and identifying untested regions. Coverage analysis guides test creation, detects dead code, and validates test adequacy in quality assurance processes. |
| ScholarGateConjunto de datos ↗ |
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