This paper provides a comprehensive literature review on the automated analysis of feature models, a key concept in software product line engineering. Feature models are information models that represent a set of products as a set of features, facilitating the management of variability and commonality. The review covers 53 primary studies published between 1990 and 2009, focusing on analysis operations, tools, paradigms, and algorithms. The authors present a conceptual framework to categorize the different proposals and identify future research directions. They discuss various analysis operations, such as void feature model, valid product, and optimization, and the automated support methods, including propositional logic, constraint programming, and description logic. The paper also highlights challenges and open research questions in the field, aiming to guide future research and practitioners in the area of automated feature model analysis.This paper provides a comprehensive literature review on the automated analysis of feature models, a key concept in software product line engineering. Feature models are information models that represent a set of products as a set of features, facilitating the management of variability and commonality. The review covers 53 primary studies published between 1990 and 2009, focusing on analysis operations, tools, paradigms, and algorithms. The authors present a conceptual framework to categorize the different proposals and identify future research directions. They discuss various analysis operations, such as void feature model, valid product, and optimization, and the automated support methods, including propositional logic, constraint programming, and description logic. The paper also highlights challenges and open research questions in the field, aiming to guide future research and practitioners in the area of automated feature model analysis.