Indexing and Efficient Instance-Based Retrieval of Process Models Using Untanglings

Process-Aware Information Systems (PAISs) support executions of operational processes that involve people, resources, and software applications on the basis of

process models

. Process models describe vast, often infinite, amounts of

process instances

, e.g., workflows supported by the systems. With the increasing adoption of PAISs, large process model

repositories

emerged in companies and public organizations. These repositories constitute significant information resources. Accurate and efficient retrieval of process models and/or process instances from such repositories is interesting for multiple reasons, e.g., searching for similar models/instances, filtering, reuse, standardization, process compliance checking, verification of formal properties, etc. This paper proposes a technique for

indexing

process models that relies on their alternative representations, called

untanglings

. We show the use of untanglings for retrieval of process models based on process instances that they specify via a solution to the

total executability problem

. Experiments with industrial process models testify that the proposed retrieval approach is up to three orders of magnitude faster than the state of the art.