Mining accurate message formats for service APIs

Abstract

APIs play a significant role in the sharing, utilization and integration of information and service assets for enterprises, delivering significant business value. However, the documentation of service APIs can often be incomplete, ambiguous, or even non-existent, hindering API-based application development efforts. In this paper, we introduce an approach to automatically mine the fine-grained message formats required in defining the APIs of services and applications from their interaction traces, without assuming any prior knowledge. Our approach includes three major steps with corresponding techniques: (1) classifying the interaction messages of a service into clusters corresponding to message types, (2) identifying the keywords of messages in each cluster, and (3) extracting the format of each message type. We have applied our approach to network traces collected from four real services which used the following application protocols: REST, SOAP, LDAP and SIP. The results show that our approach achieves much greater accuracy in extracting message formats for service APIs than current state-of-art approaches.