A Controlled Experiment on Inheritance Depth as a Cost Factor for Maintenance

In two controlled experiments we compare the performance on maintenance tasks for three equivalent programs with 0, 3, and 5 levels of inheritance. For the given tasks, which focus on understanding effort more than change effort, programs with less inheritance were faster to maintain. John Daly et al. previously reported on similar experiments on the same question with quite different results. They found that the 5-level program tended to be harder to maintain than the 0-level program, while the 3-level program was significantly easier to maintain than the 0-level program. We describe the design and setup of our experiment, the differences to the previous ones, and the results obtained. Ours and the previous experiments are different in several ways: We used a longer and more complex program, made an inheritance diagram available to the subjects, and added a second kind of maintenance task. Nevertheless, when taken together, the results suggest that there is no such thing as usefulness or harmfulness of a certain inheritance depth as such. Maintenance effort depends on other factors partly related to inheritance depth. Using a posthoc statistical analysis, we identify the number of relevant methods to be one such factor. It can be used to build a statistical prediction model of average maintenance effort that is much more powerful than a model relying on inheritance depth.