Business Process Compliance with impact constraints

IF 3 2区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information Systems Pub Date : 2024-12-10 DOI:10.1016/j.is.2024.102505

Tewabe Chekole Workneh, Pietro Sala, Romeo Rizzi, Matteo Cristani

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引用次数: 0

Abstract

Business Process Compliance is a family of methods to evaluate Business Processes in terms of the existence of one execution (one trace) that does not violate constraints superimposed on the process itself. The dual version is formulated as the superimposition of a set of constraints and consequent evaluation of the process for all the executions. These problems are relevant to a large part of actual applications, especially those in the context of regulatory compliance where we aim at verifying the process against a normative background (including, for instance, soft ones, such as guidelines, product specification, and product standards) or goals fixed by the owner of the process. In this paper we discuss one new type of compliance, that is impact compliance, devised to verify when a process respects a set of constraints, to establish that certain amounts, measuring the undesired effects of the tasks executed to implement the process, are below given limits.

In the current literature on Business Process Management, Business Process Analysis, and Business Process Compliance, this type of compliance checking process has not yet been addressed. As we demonstrate in this paper, this problem is significant and complex to address.

In particular, we show that the checking problems described above are, under certain structural conditions, polynomially solvable on deterministic machines. In general, however, the first problem is NP-complete whilst the second is polynomially solvable on deterministic machines.

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来源期刊

Information Systems 工程技术-计算机：信息系统

CiteScore

9.40

自引率

2.70%

发文量

112

审稿时长

53 days

期刊介绍： Information systems are the software and hardware systems that support data-intensive applications. The journal Information Systems publishes articles concerning the design and implementation of languages, data models, process models, algorithms, software and hardware for information systems. Subject areas include data management issues as presented in the principal international database conferences (e.g., ACM SIGMOD/PODS, VLDB, ICDE and ICDT/EDBT) as well as data-related issues from the fields of data mining/machine learning, information retrieval coordinated with structured data, internet and cloud data management, business process management, web semantics, visual and audio information systems, scientific computing, and data science. Implementation papers having to do with massively parallel data management, fault tolerance in practice, and special purpose hardware for data-intensive systems are also welcome. Manuscripts from application domains, such as urban informatics, social and natural science, and Internet of Things, are also welcome. All papers should highlight innovative solutions to data management problems such as new data models, performance enhancements, and show how those innovations contribute to the goals of the application.