Detecting approximate clones in business process model repositories

Rosa, Marcello La; Dumas, Marlon; Ekanayake, Chathura C.; García‐Bañuelos, Luciano; Recker, Jan; Hofstede, Arthur H. M. ter

doi:10.1016/j.is.2014.11.010

Cited by 30 publications

(19 citation statements)

References 44 publications

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“…However, clustering techniques always consider entire traces and thus also unnecessary duplicate tasks which are the same in all variants. In [14], the authors proposed a top-down approach that clusters the traces, discovers models for each cluster separately and uses clone detection to find tasks that are the same in all variants, preventing unnecessary duplicating tasks [15]. However, trace clustering techniques are unable to distinguish two events having the same label within a trace or a variant [12].…”

Section: Related Workmentioning

confidence: 99%

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Handling Duplicated Tasks in Process Discovery by Refining Event Labels

Fahland

Biggelaar

et al. 2016

Lecture Notes in Computer Science

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Section: Related Workmentioning

confidence: 99%

“…In this experiment, we used the default parameters: the variant threshold z v is 0.05 and the unfolding threshold z f is 0.60 for all models. We generated for size n = [10,15,20] 200 models (600 models in total). For each model, there are k = 4 transitions having the same label and that are not in a loop.…”

Section: Experimental Evaluation and Case Studymentioning

confidence: 99%

Handling Duplicated Tasks in Process Discovery by Refining Event Labels

Fahland

Biggelaar

et al. 2016

Lecture Notes in Computer Science

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“…The SMD technique [23,24] discovers hierarchies of process models related via specialization but also part-of relations. However, SMD only extracts block-structured subprocesses that occur in identical or almost identical form in two different specializations of a process.…”

Section: Automated Discovery Of Hierarchical Process Modelsmentioning

confidence: 99%

BPMN Miner: Automated discovery of BPMN process models with hierarchical structure

Conforti

Dumas

García‐Bañuelos

et al. 2016

Information Systems

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a b s t r a c tExisting techniques for automated discovery of process models from event logs generally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique, namely BPMN Miner, for automated discovery of hierarchical BPMN models containing interrupting and non-interrupting boundary events and activity markers. The technique employs approximate functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery techniques, BPMN Miner is able to detect and filter out noise in the event log arising for example from data entry errors, missing event records or infrequent behavior. Noise is detected during the construction of the subprocess hierarchy and filtered out via heuristics at the lowest possible level of granularity in the hierarchy. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.

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“…Their goal is to guide business users in understanding and adopting the concepts of a specific fragment [24]. This requires corresponding querying techniques [25] and the automatic identification of recurring fragments [26].…”

Section: Repeated Use Versus Re-use Of Process Modelsmentioning

confidence: 99%

Repeated use of process models: The impact of artifact, technological, and individual factors

Nolte

Bernhard

Recker

et al. 2016

Decision Support Systems

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Business process modeling has received a lot of attention from practitioners and researchers alike.Organizations make significant investments into process modeling in terms of training, tools and resources. Yet, having invested into creating large process model collections, process models often fall into disuse, provoking the impression that the initial investment has been lost. While previous work has aimed at exploring model re-use as a design principle, our work examines repeated use of a model as a behavior and thus aims at identifying factors that facilitate or hinder the repeated use of process models by individual users. We develop a conceptual model of factors that can influence an individual's intention to repeatedly use process models. We evaluate this model through a cross-sectional survey of process model users from a large European financial institution. Our results indicate the importance of quality and ease of understanding of process models to repeated use, alongside individual factors, such as motivation and individual expertise. We identify means that help organizations to promote the repeated use of process models, which can assist them to increase the benefits of process modeling.

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Detecting approximate clones in business process model repositories

Cited by 30 publications

References 44 publications

Handling Duplicated Tasks in Process Discovery by Refining Event Labels

Handling Duplicated Tasks in Process Discovery by Refining Event Labels

BPMN Miner: Automated discovery of BPMN process models with hierarchical structure

Repeated use of process models: The impact of artifact, technological, and individual factors

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