Predicting maintenance performance using object-oriented design complexity metrics

Abstract

The Object-Oriented (OO) paradigm has become increasingly popular in recent years. Researchers agree that, although maintenance may turn out to be easier for OO systems, it is unlikely that the maintenance burden will completely disappear. One approach to controlling software maintenance costs is the utilization of software metrics during the development phase, to help identify potential problem areas. Many new metrics have been proposed for OO systems, but only a few of them have been validated. The purpose of this research is to empirically explore the validation of three existing OO design complexity metrics and, specifically, to assess their ability to predict maintenance time. This research reports the results of validating three metrics, Interaction Level (IL), Interface Size (IS), and Operation Argument Complexity (OAC). A controlled experiment was conducted to investigate the effect of design complexity (as measured by the above metrics) on maintenance time. Each of the three metrics by itself was found to be useful in the experiment in predicting maintenance performance.