Autonomous Development of Algorithmic Concepts for Program Comprehension

Abstract

A developmental model of algorithmic concepts is proposed here for program comprehension. Unlike traditional approaches that cannot do anything beyond their predesigned representation, this model can develop its internal representation autonomously from chaos into algorithmic concepts by mimicking concept formation in the brain under an uncontrollable environment that consists of program source codes from the Internet. The developed concepts can be employed to identify what algorithm a program performs. The accuracy of such identification reached 97.15% in a given experiment.