This paper introduces a new technique for predicting latent software bugs, called change classification. Change classification uses a machine learning classifier to determine wheth...
Sunghun Kim, E. James Whitehead Jr., Yi Zhang 0001
Abstract—Change prediction helps developers by recommending program entities that will have to be changed alongside the entities currently being changed. To evaluate their accura...
Abstract—Developers often make multiple changes to software. These changes are introduced to work cooperatively or to accomplish separate goals. However, changes might not intera...
Evolving software-intensive systems from one consistent state to another is a challenging activity due to the intricate inter-dependencies among the components. In this paper, we ...
An approach for factoring source-code differences is presented. A single large difference between two versions of a program is decomposed into factors (i.e., smaller changes). The...
Michael L. Collard, Huzefa H. Kagdi, Jonathan I. M...