Dynamic variability support in context-aware workflow-based systems
- Autores: Aitor Murguzur Ibarguren
- Directores de la Tesis: Goiuria Sagardui Mendieta (dir. tes.)
, Salvador Trujillo Gonzalez (codir. tes.) - Lectura: En la Mondragon Unibertsitatea ( España ) en 2015
- Idioma: inglés
- Tribunal Calificador de la Tesis: Óscar Díaz García (presid.) , Félix Larrinaga Barrenechea (secret.) , Rafael Capilla Sevilla (voc.) , Oystein Haugen (voc.) , Hong-linh Truong (voc.)
- Enlaces
- Resumen
This dissertation proposes an approach for variant-rich workflow-based systems that can comprise context data while deferring process configuration to run time. Whereas existing early process variability approaches, like Worklets, VxBPEL, or Provop handle run-time reconfiguration, ours lets us resolve variants at execution time and supports multiple binding required for dynamic environments. Finally, unlike the specialized reconfiguration solutions for some workflow-based systems, our approach allows an automated decision making, enabling different run-time resolution strategies that intermix constraint solving and feature models.
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