When reengineering or improving an engineering process, it is important to systematically examine the process for possible weak spots. Complexity metrics, which describe how “complex” a possible part of a process is, are a means of doing so. Using them, every single element of a process (e.g. activities, resources,…) or groups of elements can be reviewed, and those exhibiting distinctive features can be further considered for improvement. Such metrics are especially of interest if no quantitative data is available but only the qualitative process architecture is at hand, e.g. as a process chart. In this paper, different metrics from software and workflow engineering (McCabe Complexity, Control-flow Complexity, Activity / Passivity) are used on a qualitative model of a process incorporating decision points. The process model is based on a Multiple-Domain Matrix extended to comprise Boolean operators that are typical for process models (i.e. AND, OR, and XOR).
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When reengineering or improving an engineering process, it is important to systematically examine the process for possible weak spots. Complexity metrics, which describe how “complex” a possible part of a process is, are a means of doing so. Using them, every single element of a process (e.g. activities, resources,…) or groups of elements can be reviewed, and those exhibiting distinctive features can be further considered for improvement. Such metrics are especially of interest if no quantitativ...
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