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.)
• Programa de doctorado: Programa Oficial de Doctorado en Ingeniería
• Materias:
  • Matemáticas
    • Ciencia de los ordenadores
      • Informática
      • Sistemas de información, diseño y componentes
• Enlaces
  • Tesis en acceso abierto en:  TESEO  eBiltegia 
• 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.