Automated program synthesis has not gained widespread acceptance among software practitioners despite considerable efforts by several researchers. We outline some of the difficulties in applying program synthesis for practical problems and argue that a careful analysis of the cost vs. benefit tradeoff is essential when considering such an approach. We describe a successful application of automated program generation for synthesizing geometric constraint satisfaction routines in the domain of mechanical CAD. We present a general framework for modeling and solving the problem, illustrate the framework using examples from the geometric constraint satisfaction domain, and describe experimental results on productivity increase using this approach. We also discuss characteristics of the problem domain and our approach that were critical for success.

An important problem in geometric reasoning is to find the configuration of a collection of geometric bodies so as to satisfy a set of given constraints. Recently, it has been suggested that this problem can be solved efficiently by symbolically reasoning about geometry. This approach, called degrees of freedom analysis, employs a set of specialized routines called plan fragments that specify how to change the configuration of a set of bodies to satisfy a new constraint while preserving existing constraints. A potential drawback, which limits the scalability of this approach, is concerned with the difficulty of writing plan fragments. In this paper we address this limitation by showing how these plan fragments can be automatically synthesized using first principles about geometric bodies, actions, and topology.