Book ChapterDOI
Process mining framework for software processes
Vladimir Rubin,CW Christian Günther,Wil M. P. van der Aalst,Ekkart Kindler,Boudewijn F. van Dongen,Wilhelm Schäfer +5 more
- Vol. 0701, pp 169-181
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TLDR
A Process Mining Framework can be used for obtaining software process models as well as for analysing and optimising them and an algorithmic approach, which arose from research on software processes, is integrated in the framework.Abstract:
Software development processes are often not explicitly modelled and sometimes even chaotic. In order to keep track of the involved documents and files, engineers use Software Configuration Management (SCM) systems. Along the way, those systems collect and store information on the software process itself. Thus, SCM information can be used for constructing explicit process models, which is called software process mining. In this paper we show that (1) a Process Mining Framework can be used for obtaining software process models as well as for analysing and optimising them; (2) an algorithmic approach, which arose from our research on software processes, is integrated in the framework.read more
Citations
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Journal ArticleDOI
Discovering simulation models
TL;DR: A combination of process mining techniques is used to discover multiple perspectives of the process from historic data and integrate them into a comprehensive simulation model, represented as a colored Petri net (CPN) and used to analyze the process.
Journal ArticleDOI
Process mining techniques and applications – A systematic mapping study
Cleiton dos Santos Garcia,Alex Meincheim,Elio Ribeiro Faria Junior,Marcelo Rosano Dallagassa,Denise Maria Vecino Sato,Denise Maria Vecino Sato,Deborah Ribeiro Carvalho,Eduardo Alves Portela Santos,Edson Emílio Scalabrin +8 more
TL;DR: It is possible to observe that the most active research topics are associated with the process discovery algorithms, followed by conformance checking, and architecture and tools improvements, and finally application domains among different business segments are reported on.
Proceedings ArticleDOI
Process Mining Software Repositories
TL;DR: This work proposes to apply process mining techniques, originally developed for business process analysis, to address the challenge of successful information extraction by addressing the necessity to simultaneously analyze different repositories and to combine the information obtained.
Detection and Prediction of Errors in EPC Business Process Models.
TL;DR: A rotary drive mechanism selectively and rotationally drives at least first and second bodies which are to be driven.
Journal ArticleDOI
Comprehensive rule-based compliance checking and risk management with process mining
TL;DR: This paper proposes a comprehensive rule-based process mining approach for a timely investigation of a complete set of enriched process event data and elaborates a two-dimensional business rule taxonomy that serves as a source of business rules for the comprehensiveRule-based compliance checking approach.
References
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Proceedings ArticleDOI
Mining sequential patterns
TL;DR: Three algorithms are presented to solve the problem of mining sequential patterns over databases of customer transactions, and empirically evaluating their performance using synthetic data shows that two of them have comparable performance.
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Workflow mining: discovering process models from event logs
TL;DR: A new algorithm is presented to extract a process model from a so-called "workflow log" containing information about the workflow process as it is actually being executed and represent it in terms of a Petri net.
Journal ArticleDOI
Process modeling
TL;DR: In this article, software process modeling will be used as an example application for describing the current status of process modeling, issues for practical use, and the research questions that remain ahead.
Journal ArticleDOI
Two case studies of open source software development: Apache and Mozilla
TL;DR: This work examines data from two major open source projects, the Apache web server and the Mozilla browser, and quantifies aspects of developer participation, core team size, code ownership, productivity, defect density, and problem resolution intervals for these OSS projects.
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