Process modeling

Reviewer: Robert Baumgartner

The authors start with a description of how process modeling is distinguished from modeling in other areas of information science. They argue that newer uses of information technology extend computer use beyond transaction processing into communication and coordination. As a consequence, even manual organizational processes must be modeled. Therefore, an important property of process modeling is that many of the phenomena modeled must be performed by a human rather than a machine. This statement is true for business process modeling and for software process modeling. The latter is used throughout the paper as an example application. This choice is one of the weaknesses of the paper; it would be more useful if examples of business processes had been discussed as well. After a brief discussion of the uses for process models, the paper continues with a description of the conceptual framework. Because no consensus exists on the constructs that form a process model, the authors have abstracted, from various papers, a description of the most frequently used elements, which are then used to give a more precise definition of the term “process model.” The kinds of information that people usually want to extract from a process model include what is going to be done, who is going to do it, when and where it will be done, how and why it will be done, and who is dependent on its being done. These questions form the basis of the different perspectives—functional, behavioral, organizational, and informational—in process representation. The authors use these perspectives in the following section to evaluate process modeling languages. The main part of the paper discusses different process modeling paradigms. Starting from a description of programming models, the authors give an overview of functional models, plan-based models, Petri net models, and quantitative models. With the exception of programming models, where a rather large number of languages exist, many of the models are represented by one example. The authors included some discussion of the usefulness of these models, but I would have liked a more detailed discussion of this issue. The authors continue with a description of the issues pertinent to process modeling. For example, the level of formality required may depend on the purpose served by the process model and on whether the task is performed by a human or a machine. Similarly, the granularity of a process step may depend on the purpose of the model and on whether a human or a machine performs the step. The last section discusses future directions. I found the discussion of process-based software environments most interesting. On the whole, the paper provides a good overview of process modeling with a special emphasis on software process modeling.