A Runtime Analysis of Graph-Theoretical Algorithms to Detect Patterns in Process Model Collections

Becker Jörg, Breuker Dominic, Delfmann Patrick, Dietrich Hanns-Alexander, Steinhorst Matthias


Abstract
Pattern detection serves different purposes in managing large collections of process models, ranging from syntax checking to compliance validation. This paper presents a runtime analysis of four graph-theoretical algorithms for (frequent) pattern detection. We apply these algorithms to large collections of process and data models to demonstrate that, despite their theoretical intractability, they are able to return results within (milli-) seconds. We discuss the relative performance of these algorithms and their applicability in practice.

Keywords
Conceptual Model Analysis, Subgraph Isomorphism, Frequent Subgraph Detection, Pattern Matching



Publication type
Conference Paper

Peer reviewed
Yes

Publication status
Published

Year
2012

Conference
2nd International Workshop on Process Model Collections (PMC) 2012

Venue
Tallinn, Estonia

Book title
Business Process Management Workshops

Editor
Marcello La Rosa, Pnina Soffer

Start page
489

End page
500

Volume
132

Title of series
Lecture Notes in Business Information Processing

Publisher
Springer

Place
Berlin, Heidelberg

Language
English

DOI