Identifying key entities has many implications for software understanding and controlling and reducing maintenance costs.However the existing methods only focus on identifying key classes.Little work has been done on the identification of key entities at the other levels.Further the existing work also failed to reveal the relationships between key classes and external quality attributes.In this paper

we introduce a novel method IDEEP (IDEntifying kEy Packages using weighted PageRank algorithm) to identify the key packages.IDEEP uses a weighted and directed software network to describe packages and their dependencies

proposes a new metric PR (PackageRank) to quantify the package importance

and introduces a weighted PageRank algorithm to compute PR values.Our experiments are carried out on six Java software systems.First we analyze the correlation between PR values and other centrality metrics such as betweenness

closeness and degree.Second we use a weighted version of the susceptible-infectious-recovered model to examine the spreading influence of each node.The results show that our method is better than other six methods.Further

we reveal the relationships between key packages and their understandability and show that the key packages identified by our method are more meaningful from a software engineering perspective.