An empirical study on object-oriented metrics and software evolution in order to reduce testing costs by predicting change-prone classes

Software maintenance cost is typically more than fifty percent of the cost of the total software life cycle and software testing plays a critical role in reducing it. Determining the critical parts of a software system is an important issue, because they are the best place to start testing in order to reduce cost and duration of tests. Software quality is an important key factor to determine critical parts since high quality parts of software are less error prone and easy to maintain. As object oriented software metrics give important evidence about design quality, they can help software engineers to choose critical parts, which should be tested firstly and intensely. In this paper, we present an empirical study about the relation between object oriented metrics and changes in software. In order to obtain the results, we analyze modifications in software across the historical sequence of open source projects. Empirical results of the study indicate that the low level quality parts of a software change frequently during the development and management process. Using this relation we propose a method that can be used to estimate change-prone classes and to determine parts which should be tested first and more deeply.