Predicting software stability using case-based reasoning

Predicting stability in object-oriented (OO) software, i.e., the ease with which a software item can evolve while preserving its design, is a key feature for software maintenance. We present a novel approach which relies on the case-based reasoning (CBR) paradigm. Thus, to predict the chances of an OO software item breaking downward compatibility, our method uses knowledge of past evolution extracted from different software versions. A comparison of our similarity-based approach to a classical inductive method such as decision trees, is presented which includes various tests on large datasets from existing software.