Title
Detection of naming convention violations in process models for different languages
Abstract
Companies increasingly use business process modeling for documenting and redesigning their operations. However, due to the size of such modeling initiatives, they often struggle with the quality assurance of their model collections. While many model properties can already be checked automatically, there is a notable gap of techniques for checking linguistic aspects such as naming conventions of process model elements. In this paper, we address this problem by introducing an automatic technique for detecting violations of naming conventions. This technique is based on text corpora and independent of linguistic resources such as WordNet. Therefore, it can be easily adapted to the broad set of languages for which corpora exist. We demonstrate the applicability of the technique by analyzing nine process model collections from practice, including over 27,000 labels and covering three different languages. The results of the evaluation show that our technique yields stable results and can reliably deal with ambiguous cases. In this way, this paper provides an important contribution to the field of automated quality assurance of conceptual models. We present an automatic technique for detecting violations of naming conventions.The technique is based on text corpora and independent of linguistic resources.Because of its design, the approach can be easily adapted to other languages.The evaluation includes 27,000 labels and three different languages.
Year
DOI
Venue
2013
10.1016/j.dss.2013.06.014
Decision Support Systems
Keywords
Field
DocType
different language,process model element,linguistic aspect,business process modeling,model collection,model property,automated quality assurance,technique yields stable result,process model collection,convention violation,conceptual model,automatic technique,natural language processing
Data mining,Conceptual model,Computer science,Convention,Work in process,Text corpus,Artificial intelligence,Natural language processing,Business process modeling,WordNet,Quality assurance
Journal
Volume
Issue
ISSN
56
C
0167-9236
Citations 
PageRank 
References 
22
0.72
66
Authors
5
Name
Order
Citations
PageRank
Henrik Leopold150436.19
Rami-Habib Eid-Sabbagh2656.16
Jan Mendling34250245.37
Leonardo Guerreiro Azevedo47915.52
Fernanda Araujo Baião517632.72