Adopting the Cognitive Complexity Measure for Business Process Models

Author

Gruhn, Volker ; Laue, Ralf

Author_Institution

Leipzig Univ.

Volume

1

fYear

2006

fDate

17-19 July 2006

Firstpage

236

Lastpage

241

Abstract

Business process models, often modelled using graphical languages like UML, serve as a base for communication between the stakeholders in the software development process. To fulfil this purpose, they should be easy to understand and easy to maintain. For this reason, it is useful to have measures that can give us some information about understandability, analyzability and maintainability of a business process model. Shao and Wang (2003) have proposed a cognitive complexity measure. It can be used to estimate the comprehension effort for understanding software. This paper discusses how these research results can be extended in order to analyze the cognitive complexity of graphical business process models

Keywords

corporate modelling; reverse engineering; software metrics; business process model; cognitive complexity measure; complexity metrics; software development process; software understanding; Business communication; Business process re-engineering; Communication system control; Error analysis; Information analysis; Predictive models; Process control; Software measurement; Telematics; Unified modeling language; business process models; cognitive complexity; complexity metrics;

fLanguage

English

Publisher

ieee

Conference_Titel

Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

1-4244-0475-4

Type

conf

DOI

10.1109/COGINF.2006.365702

Filename

4216417