Many dynamic analysis approaches to specification mining that ex-tract behavioral models from execution traces, do not consider ob-ject identities which limit their power when used to analyze traces of general object oriented programs. In this work we present a novel specification mining approach that considers object identi-ties, and, moreover, generalizes from specifications involving con-crete objects to their symbolic class-level abstractions. Our ap-proach uses data mining methods to extract significant scenario-based specifications in the form of Damm and Harel’s live sequence charts (LSC), a formal and expressive extension of classic sequence diagrams. We guarantee that all mined symbolic LSCs are sig-nificant (statistically sound) and all significant symbolic LSCs are mined (statistically complete). The technique can potentially be ap-plied to general object oriented programs to reveal expressive and useful reverse-engineered candidate specifications. 1
