Understanding Declare models: strategies, pitfalls, empirical results

Abstract

Declarative approaches to business process modeling are regarded as well suited for highly volatile environments, as they enable a high degree of flexibility. However, problems in understanding and maintaining declarative process models often impede their adoption. Likewise, little research has been conducted into the understanding of declarative process models. This paper takes a first step toward addressing this fundamental question and reports on an empirical investigation consisting of an exploratory study and a follow-up study focusing on the system analysts' sense-making of declarative process models that are specified in Declare. For this purpose, we distributed real-world Declare models to the participating subjects and asked them to describe the illustrated process and to perform a series of sense-making tasks. The results of our studies indicate that two main strategies for reading Declare models exist: either considering the execution order of the activities in the process model, or orienting by the layout of the process model. In addition, the results indicate that single constraints can be handled well by most subjects, while combinations of constraints pose significant challenges. Moreover, the study revealed that aspects that are similar in both imperative and declarative process modeling languages at a graphical level, while having different semantics, cause considerable troubles. This research not only helps guiding the future development of tools for supporting system analysts, but also gives advice on the design of declarative process modeling notations and points out typical pitfalls to teachers and educators of future systems analysts.

Comprehension of Procedural Visual Business Process Models

“…We focus on procedural process models because they follow the same underlying representation paradigm. An increasing number of studies also investigate declarative process models (e.g., Haisjackl and Zugal 2014;Haisjackl et al 2016;Zugal et al 2015). In comparison to procedural (or imperative) process models, which specify all possible alternatives for execution, declarative process models focus on modeling the constraints that prevent undesired alternatives for execution (Fahland et al 2009).…”

The Semantics of Hybrid Process Models

“…Consider, for example, that many Declare constraints take on arrow-like shapes, similar to how the transition relation is visualized in a Petri net. In work on sense-making of declarative models, one of the major issues identified occurs, indeed, when a user is confronted with a combination of constraint arrows [9]. We also feel that process decomposition is a natural way to separate complexity, allows for the re-use of model fragments, and supports both bottom-up and topdown modelling.…”

Enabling Flexible and Robust Business Process Automation for the Agile Enterprise

“…The latter enables the reuse of ad hoc changes in similar situations [25]. The analysis of these logs by process engineers or process intelligence tools allows for the discovery of malfunctions or bottlenecks, which often leads to an evolution of the process model (6). The latter is supported through versioning as well as the ability of dynamically migrating already running process instances.…”

“…In practice, however, business processes have become increasingly complex and dynamic, demanding for a more agile approach acknowledging that in dynamic environments process models quickly become outdated and, hence, a closer interweaving of modeling and execution is required. Therefore, PAISs not only need to be able to deal with exceptions [20], change the execution of single business cases on the fly [17], efficiently deal with uncertainty [6], and cope with variability [1,7], but must also support the evolution of implemented business processes over time [19].…”