Predicting Next Changes at the Fine-Grained Level

Abstract

Changing source code is not an easy task. Developers occasionally change source code incorrectly. Such mistakes entail additional cost in having to reedit the source code correctly, and repeated changes themselves can be a vulnerability to software quality. We are conducting research into realizing automated code changing as a countermeasure for human errors. As the first step of this research, we propose a technique to predict the types of program elements deleted and added in a next change to Java methods. This technique is designed to support developers in deciding how to change source code after they have identified a method to be changed. We evaluated predictions using the proposed technique with two thresholds, which are sizes of source code changes. For predictions with the smaller threshold where only a single type of program element was added or deleted, the accuracy of the proposed technique was 74% -- 85%. However, for the larger threshold, where 5 or fewer types of program elements were added or deleted, the accuracy was 44% -- 48%.