Detection of naming convention violations in process models for different languages
Detection of naming convention violations in process models for different languages
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DOI：
10.1016/j.dss.2013.06.014
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发表时间：
2013-12
期刊：
影响因子：
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通讯作者：
H. Leopold;Rami-Habib Eid-Sabbagh;J. Mendling;L. Azevedo;F. Baião
中科院分区：
文献类型：
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作者：
H. Leopold;Rami-Habib Eid-Sabbagh;J. Mendling;L. Azevedo;F. Baião
公司越来越多地使用业务流程建模来记录和重新设计他们的运营。然而，由于这种建模计划的规模，他们经常与他们的模型集合的质量保证作斗争。虽然许多模型属性已经可以自动检查，但在检查语言方面（如流程模型元素的命名约定）的技术方面存在明显的差距。在本文中，我们解决这个问题，通过引入一个自动检测违反命名约定的技术。这种技术是基于文本语料库和独立的语言资源，如WordNet。因此，它可以很容易地适用于现有语料库的广泛语言。我们通过分析来自实践的9个过程模型集合来证明该技术的适用性，其中包括超过27，000个标签，并涵盖三种不同的语言。评估的结果表明，我们的技术产生稳定的结果，可以可靠地处理模棱两可的情况下。通过这种方式，本文提供了一个重要的贡献领域的自动化质量保证的概念模型。
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.