This paper describes a novel approach to detect variability in a software product line from its change history such that software changes are converted to vectors and a factor analysis is applied. To show the applicability of our approach, we conducted experimental applications using a software repository of automotive engine control software. As a result of the experiments, variability is detected from the change history of products.
['Kentaro Yoshimura', 'Fumio Narisawa', 'Koji Hashimoto', 'Tohru Kikuno']
FAVE: factor analysis based approach for detecting product line variability from change history