Modelled on software engineering: flexible parametric models in the practice of architecture

In this thesis I consider the relationship between the design of software and the design of flexible parametric models.There is growing evidence that parametric models employed in practice lack the flexibility to accommodate certain design changes. When a designer attempts to change a model’s geometry (by modifying the model’s underlying functions and parameters) they occasionally end up breaking the model. The designer is then left with a dilemma: spend time building a new model, or abandon the changes and revise the old model. Similar dilemmas exist in software engineering. Despite these shared concerns, Robert Woodbury (2010, 66) states that there is currently “little explicit connection” between the practice of software engineering and the practice of parametric modelling. In this thesis I consider, using a reflective practice methodology, how software engineering may inform parametric modelling. Across three case studies I take aspects of the software engineering body of knowledge (language paradigms; structured programming; and interactive programming) and apply them to the design of parametric models for the Sagrada Família, the Dermoid pavilion, and the Responsive Acoustic Surface. In doing so I establish three new parametric modelling methods. The contribution of this research is to show there are connections between the practice of software engineering and the practice of parametric modelling. These include the following:• Shared challenges: Both practices involve unexpected changes occurring within the rigid logic of computation. • Shared research methods: Research methods from software engineering apply to the study of parametric modelling.• Shared practices: The software engineering body of knowledge seems to offer a proven pathway for improving the practice of parametric modelling.These connections signal that software engineering is an underrepresented and important precedent for architects using parametric models; a finding that has implications for how parametric modelling is taught, how parametric models are integrated with practice, and for how researchers study and discuss parametric modelling.