Distributing Computationally Expensive Matching of Requirements to Capability Models

In this paper, we present a distributed way to automatically map users´ requirements to reference process models. In a prior paper [9], we presented a tool called Process Model Requirements Gap Analyzer (ProcGap), which combines natural language processing, information retrieval, and semantic reasoning to automatically match and map textual requirements to domain-specific process models. Although the tool proved beneficial to users in reusing prior knowledge, by making it easy to use process models, the tool has one main drawback. It takes a long time to compare a very large requirements document, one that has a few thousand requirements, to a process model hierarchy with a few thousand capabilities. In this paper, we present how we solved this problem using Apache Hadoop. Apache Hadoop allows ProcGap to distribute matching task across several machines, increasing the tool´s performance and usability. We present the performance comparison of running ProcGap on a single-machine, and our distributed version.