Improving Automated Mapping in Reflexion Models Using Information Retrieval Techniques

The reflexion model technique supports structural conformance checking of software systems. The scalability of the technique is limited by the requirement for developers to provide a mapping between implementation entities and high-level modules. Such mapping is usually based on regular expressions, and it must also be updated as the system evolves. Automated mapping techniques exist but are solely based on structural dependencies. In this paper, we introduce an automated mapping technique for reflexion models based on information retrieval techniques. It makes use of source code vocabulary and their similarity to the vocabulary of high-level modules. Two case studies conducted across four systems show that the nature of the module view influences which technique performs best. Results also show that combining both mapping techniques into a two step-mapping algorithm generally increases recall, while keeping precision similar to the best approach used in isolation.