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| Architekturschmalerkennung× | Messung technischer Schulden× | |
|---|---|---|
| Fachgebiet | Softwaretechnik | Softwaretechnik |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 2009 | 1992 |
| Urheber≠ | Martin Fowler and García et al. | Ward Cunningham |
| Typ≠ | pattern-based analysis | quantitative assessment |
| Wegweisende Quelle≠ | Fowler, M. (2018). Code smell. Martin Fowler's Website. link ↗ | Cunningham, W. (1992). The WyCash Portfolio Management System. OOPSLA 92 Experience Report. link ↗ |
| Aliasnamen | design smell detection, architectural debt analysis, system quality assessment | debt metrics, code health scoring, maintenance burden assessment |
| Verwandt | 4 | 4 |
| Zusammenfassung≠ | Architecture smells are recurring patterns in system structure that indicate potential design problems. Introduced by García et al. (2009), these patterns signal violations of architectural principles (modularity, independence, abstraction) at system scale. Detection combines code metrics, dependency analysis, and pattern recognition to identify smells early, guiding refactoring and architectural improvements. | Technical debt represents accumulated shortcuts, deferred maintenance, and design compromises that incur future costs through slower development, higher defect rates, and deployment difficulty. Introduced by Ward Cunningham (1992), technical debt measurement quantifies these burdens using metrics like code complexity, duplication, test coverage gaps, and maintainability indices. Organizations use debt measurement to balance immediate delivery with long-term sustainability. |
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