Program comprehension in generative programming: a history of grand challenges

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, the author presents a historical review of the grand challenges, results, and outlook for GP as they pertain to PC.