Discovering System Dynamics Simulation Models Using Process Mining

Pourbafrani, Mahsa; Aalst, Wil M. P. van der

doi:10.1109/access.2022.3193507

Cited by 10 publications

(5 citation statements)

References 25 publications

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“…However, most simulation-based approaches, including system dynamics, rely heavily on users and their understanding of the system. Each level can be used for different simulation techniques, as proposed in where the results of coarse-grained simulations are used to update processes at detailed levels and later simulate the DES models at operational levels (Pourbafrani & Van der Aalst, 2022a).…”

Section: Entrepreneurship and Sustainability Issuesmentioning

confidence: 99%

Reduction of cybersecurity risk via evaluating users' behaviour

Korauš,

Špitalský,

Török

et al. 2024

JESI

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Since the 1990s, process analysis has attained a fundamental position among business management approaches. With the gradual development and expansion of digitalization in businesses that have begun to use advanced information systems, a demand also arose to survey the processes within companies, including retrospectively from the digital records of information systems. This requirement laid the foundation for the emergence of the scientific discipline known today as Process Mining. In the presented article, we introduce its basic concepts and point out the possibility of using them in the field of security analysis of the log of a general system, which creates digital records of its operation (a so-called journal or log). The result of using Process Mining methods is identifying unrecorded processes running in a system and various deviations from the expected system operation, which may signal security threats to the system itself or its operator. In the battle against hybrid threats, many resources are explicitly devoted to protecting cyberspace. The approach proposed in this article allows a system to be analysed as a whole, identifying patterns of behaviour that would not otherwise arouse suspicion in individual steps but, as a sequence of separate steps (processes), do not fall into the expected pattern of system behaviour. This can be used as a long-term sustainable concept in the fight against hybrid threats. An analysis of a system's behavior can be built on continuous "learning" by labelling newly discovered processes as safe or unsafe, ensuring the long-term sustainability of this approach. The main advantage of the proposed analyses is that they run as an oversight of the system itself, analysing it only based on records from its event log. Therefore, no interventions are needed in the architecture and source code of the analysed system, and the analyses do not affect its operation or data.

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Section: Entrepreneurship and Sustainability Issuesmentioning

confidence: 99%

Reduction of cybersecurity risk via evaluating users' behaviour

Korauš,

Špitalský,

Török

et al. 2024

JESI

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“…On the other hand, it cannot be used to assess coarse-grained BPS models, e.g. based on system dynamics [20], unless these are refined to generate event logs.…”

Section: Business Process Simulation Modelsmentioning

confidence: 99%

Can I Trust My Simulation Model? Measuring the Quality of Business Process Simulation Models

Chapela-Campa,

Benchekroun,

Baron

et al. 2023

Lecture Notes in Computer Science

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Business Process Simulation (BPS) is an approach to analyze the performance of business processes under different scenarios. For example, BPS allows us to estimate what would be the cycle time of a process if one or more resources became unavailable. The starting point of BPS is a process model annotated with simulation parameters (a BPS model). BPS models may be manually designed, based on information collected from stakeholders and empirical observations, or automatically discovered from execution data. Regardless of its origin, a key question when using a BPS model is how to assess its quality. In this paper, we propose a collection of measures to evaluate the quality of a BPS model w.r.t. its ability to replicate the observed behavior of the process. We advocate an approach whereby different measures tackle different process perspectives. We evaluate the ability of the proposed measures to discern the impact of modifications to a BPS model, and their ability to uncover the relative strengths and weaknesses of two approaches for automated discovery of BPS models. The evaluation shows that the measures not only capture how close a BPS model is to the observed behavior, but they also help us to identify sources of discrepancies.

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“…Process mining technology can use historical event logs recorded from information systems to describe and model real processes [22]. Through importing and analyzing the event log, we can determine the dependencies between all tasks in the log and establish a sequence relation matrix to store these relations.…”

Section: Instantiation Analysis Of Process Acquisitionmentioning

confidence: 99%

A Software Testing Workflow Analysis Tool Based on the ADCV Method

Mao,

Han,

et al. 2023

Electronics

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Based on two progressive aspects of the modeling problems in business process management (BPM), (1) in order to address the increasing complexity of user requirements on workflows underlying various BPM application scenarios, a more verifiable fundamental modeling method must be invented; (2) to address the diversification of software testing processes, more formalized advanced modeling technology must also be applied based on the fundamental modeling method. Aiming to address these modeling problems, this paper first proposes an ADCV (acquisition, decomposition, combination, and verification) method that runs through the core management links of four types of business processes (mining, decomposition, recombination, and verification) and then describes the compositional structure of the ADCV method and the design of corresponding algorithms. Then, the software testing workflow is managed and monitored using the method, and the corresponding analysis tool is implemented based on Petri nets. At the same time, the tool is applied to the case processing of the software testing workflow. Specifically, the workflow models are established successively through ADCV during the process of business iteration. Then, the analysis tool developed with the ADCV method, the model–view–controller (MVC) design pattern, and Java Swing technology are applied to instances of the software testing workflow to realize the modeling and management of the testing processes. Thus, the analysis tool can guarantee the accuracy of the parameter estimations of related software reliability growth models (SRGMs) and ultimately improve the quality of software products.

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Discovering System Dynamics Simulation Models Using Process Mining

Cited by 10 publications

References 25 publications

Reduction of cybersecurity risk via evaluating users' behaviour

Reduction of cybersecurity risk via evaluating users' behaviour

Can I Trust My Simulation Model? Measuring the Quality of Business Process Simulation Models

A Software Testing Workflow Analysis Tool Based on the ADCV Method

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