Translating BPMN to Business Rules

Al-Ali, Hamda; Damiani, Ernesto; Al‐Qutayri, Mahmoud; Abu-Matar, Mohammad; Mizouni, Rabeb

doi:10.1007/978-3-319-74161-1_2

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…Saruwatari et al, 33 highlighted the difficulty to extract business rules from general purpose programming languages and suggested to analyze the execution logs instead. Other authors have put an emphasis on high‐level specification languages, namely: Deesukying and Vatanawood 34 worked in the context of Petri Nets, Skersys et al 35 and Danenas et al 36 focused on UML, and Mickeviciute et al 37 and Al‐Ali et al 38 specialized in BPMN. The work by Karaa et al 39 is interesting in the context of UML since it presented an improved approach to transform business rules from natural language that are specified within a user's requirements document into an UML class diagram, automatically.…”

Section: Related Workmentioning

confidence: 99%

On the design of an advanced business rule engine

Jiménez

Corchuelo

2022

Softw Pract Exp

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Business rules govern how well‐managed companies perform every day. They are expected to be written in natural language because they are devised by business people. That makes it difficult to translate them automatically into executable rules that can be integrated into typical information systems. Our industrial and academic research concludes that the current tools have a number of problems, namely: many of them do not pay any attention to the SBVR standard; some of them are not multi‐language; most of them cannot achieve perfect parsing accuracy; some of them are not domain agnostic; some of them use proprietary technologies; some of them do not produce executable rules; and none supports exploratory what‐if analyses natively. In this article, we present Tier‐Rules, which is a system that overcomes the previous problems. We also report on an industrial case study that helps illustrate it in practice.

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Section: Related Workmentioning

confidence: 99%

On the design of an advanced business rule engine

Jiménez

Corchuelo

2022

Softw Pract Exp

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“…This off-line analysis is not suitable for cases which are still in the pipeline. An open research question is whether current algorithms to abstract models from logs are scalable enough to handle data streams [155,161].…”

Section: Data Analysis and Modellingmentioning

confidence: 99%

Big Data Semantics

et al. 2018

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Big Data technology has discarded traditional data modelling approaches as no longer applicable to distributed data processing. It is, however, largely recognised that Big Data impose novel challenges in data and infrastructure management. Indeed, multiple components and procedures must be coordinated to ensure a high level of data quality and accessibility for the application layers, e.g. data analytics and reporting. In this paper, the third of its kind co-authored by mem-

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“…5, we present our exten-1 Such organizations are subject to data protection regulations from a variety of organizations ranging from the European Union (Data Retention Directive) to national and international law enforcement agencies. Regulations explicitly prescribe the deployment of AC mechanisms that prevent unauthorized access to clients' critical information [14,15] sion to XACML, while Sect. 6 describes our enforcement mechanism in detail.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Access Control to Semantics-Aware Streamed Process Logs

et al. 2019

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Business process logs are composed of event records generated, collected and analyzed at different locations, asynchronously and under the responsibility of different authorities. Their analysis is often delegated to auditors who have a mandate for monitoring processes and computing metrics but do not always have the rights to access the individual events used to compute them. A major challenge of this scenario is reconciling the requirements of privacy and access control with the need to continuously monitor and assess the business process. In this paper, we present a model, a language and a software toolkit for controlling access to process data where logs are made available as streams of RDF triples referring to some company-specific business ontology. Our approach is based on the novel idea of dynamic enforcement: we incrementally build dynamic filters for each process instance, based on the applicable access control policy and on the current prefix of the event stream. The implementation and performance validation of our solution is also presented.

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Translating BPMN to Business Rules

Cited by 6 publications

References 12 publications

On the design of an advanced business rule engine

On the design of an advanced business rule engine

Big Data Semantics

Dynamic Access Control to Semantics-Aware Streamed Process Logs

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