Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Метрики сложности программного обеспечения× | Анализ покрытия кода× | |
|---|---|---|
| Область | Программная инженерия | Программная инженерия |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1976 | 1988 |
| Автор метода≠ | Thomas J. McCabe | Test Coverage Community |
| Тип≠ | quantitative measurement | measurement and analysis |
| Основополагающий источник≠ | 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 ↗ |
| Другие названия≠ | code complexity analysis, complexity measurement | coverage metrics, test coverage, instrumentation-based measurement |
| Связанные | 4 | 4 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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