Estimating Global Completeness of Event Logs: A Comparative Study

Pei, Jisheng; Wen, Lijie; Yang, Hu; Wang, Jianmin; Yao, Xiaojun

doi:10.1109/tsc.2018.2805912

Cited by 9 publications

(1 citation statement)

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“…Process mining is a technique for extracting useful information from workflow logs and providing an interface between process models and event data [20], which is used by many data-driven organizations to improve performance or ensure compliance [21]. In the application of the α algorithm, the task in the log is considered an atomic activity, and the execution status of the task (the start status and complete status) is not considered, which is not conducive to the detection of the parallel relation between tasks.…”

Section: α S Algorithm Based On Event Statusmentioning

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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Section: α S Algorithm Based On Event Statusmentioning

confidence: 99%