| Title |
How do humans inspect BPMN models: an exploratory study
|
|---|---|
| Published in |
Software and Systems Modeling, October 2016
|
| DOI | 10.1007/s10270-016-0563-8 |
| Pubmed ID | |
| Authors |
Cornelia Haisjackl, Pnina Soffer, Shao Yi Lim, Barbara Weber |
| Abstract |
Even though considerable progress regarding the technical perspective on modeling and supporting business processes has been achieved, it appears that the human perspective is still often left aside. In particular, we do not have an in-depth understanding of how process models are inspected by humans, what strategies are taken, what challenges arise, and what cognitive processes are involved. This paper contributes toward such an understanding and reports an exploratory study investigating how humans identify and classify quality issues in BPMN process models. Providing preliminary answers to initial research questions, we also indicate other research questions that can be investigated using this approach. Our qualitative analysis shows that humans adapt different strategies on how to identify quality issues. In addition, we observed several challenges appearing when humans inspect process models. Finally, we present different manners in which classification of quality issues was addressed. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 69 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 15 | 22% |
| Student > Bachelor | 9 | 13% |
| Student > Ph. D. Student | 8 | 12% |
| Researcher | 6 | 9% |
| Student > Doctoral Student | 5 | 7% |
| Other | 14 | 20% |
| Unknown | 12 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 28 | 41% |
| Business, Management and Accounting | 9 | 13% |
| Engineering | 9 | 13% |
| Agricultural and Biological Sciences | 2 | 3% |
| Economics, Econometrics and Finance | 2 | 3% |
| Other | 4 | 6% |
| Unknown | 15 | 22% |
Attention Score in Context
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#19,246,640
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Outputs of similar age from Software and Systems Modeling
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