Despite the widespread use of domain models, the modeling process remains underexplored, particularly regarding the interactions among agents, products, and activities. Building on prior work that identified 16 recurrent moments of dissatisfaction (“pain points”) experienced by modelers during these interactions, this study offers a deeper analysis to clarify the significance of these pain points and support improvements in modeling practice. Through an online survey of 49 modelers, the study provides empirical evidence on the frequency of these moments, the reasons behind the frustrations they cause, and the strategies modelers use to address them. The descriptive analysis offers valuable insights into these aspects, revealing interesting patterns among modelers. These findings have implications for practice and academia, offering a foundation to enhance the modeling experience and improve the value of domain modeling efforts.

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Mapping the Pain: How Modelers Experience and Respond to Common Domain Modeling Frustrations

  • Isadora Valle,
  • Tiago Prince Sales,
  • Eduardo Guerra,
  • Maya Daneva,
  • Luiz Olavo Bonino da Silva Santos,
  • Henderik Proper,
  • Giancarlo Guizzardi

摘要

Despite the widespread use of domain models, the modeling process remains underexplored, particularly regarding the interactions among agents, products, and activities. Building on prior work that identified 16 recurrent moments of dissatisfaction (“pain points”) experienced by modelers during these interactions, this study offers a deeper analysis to clarify the significance of these pain points and support improvements in modeling practice. Through an online survey of 49 modelers, the study provides empirical evidence on the frequency of these moments, the reasons behind the frustrations they cause, and the strategies modelers use to address them. The descriptive analysis offers valuable insights into these aspects, revealing interesting patterns among modelers. These findings have implications for practice and academia, offering a foundation to enhance the modeling experience and improve the value of domain modeling efforts.