Introducing Learning into Automatic Program Comprehension
Petri M. Gerdt, Jorma Sajaniemi
Abstract: Automatic program comprehension applications, which try to extract programming knowledge from program code, share many features of human program comprehension models. However, the human trait of learning seems to be missing among the shared features. We present an approach to integrate machine learning techniques into automatic program comprehension, and present an example implementation in the context of automatic analysis of roles of variables.