Abstract
The communities of Generative Programming (GP) and Program Comprehension (PC) look at similar problems: GP derives a program from a specification, PC derives a specification from a program. A basic difference between the two is GP's use of specific knowledge representations and mental models that are essential for program synthesis. In this paper, I present a historical review of the Grand Challenges, results, and outlook for GP as they pertain to PC.