The RALph miner for automated discovery and verification of resource-aware process models

Automated process discovery is a technique that extracts models of executed processes from event logs. Logs typically include information about the activities performed, their timestamps and the resources that were involved in their execution. Recent approaches to process discovery put a special emp...

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Vydáno v:Software and systems modeling Ročník 19; číslo 6; s. 1415 - 1441
Hlavní autoři: Cabanillas, Cristina, Ackermann, Lars, Schönig, Stefan, Sturm, Christian, Mendling, Jan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2020
Springer Nature B.V
Témata:
Automation
Compilers
Computer Science
Information Systems Applications (incl.Internet)
Interpreters
IT in Business
Programming Languages
Programming Techniques
Software Engineering
Software Engineering/Programming and Operating Systems
Special Section Paper
Verification
Process mining
Resource assignment
Organisational mining
Process verification
RALph
Resource mining
Model checking
ISSN:1619-1366, 1619-1374
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Shrnutí:Automated process discovery is a technique that extracts models of executed processes from event logs. Logs typically include information about the activities performed, their timestamps and the resources that were involved in their execution. Recent approaches to process discovery put a special emphasis on (human) resources, aiming at constructing resource-aware process models that contain the inferred resource assignment constraints. Such constraints can be complex and process discovery approaches so far have missed the opportunity to represent expressive resource assignments graphically together with process models. A subsequent verification of the extracted resource-aware process models is required in order to check the proper utilisation of resources according to the resource assignments. So far, research on discovering resource-aware process models has assumed that models can be put into operation without modification and checking. Integrating resource mining and resource-aware process model verification faces the challenge that different types of resource assignment languages are used for each task. In this paper, we present an integrated solution that comprises (i) a resource mining technique that builds upon a highly expressive graphical notation for defining resource assignments; and (ii) automated model-checking support to validate the discovered resource-aware process models. All the concepts reported in this paper have been implemented and evaluated in terms of feasibility and performance.
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ISSN:1619-1366
1619-1374
DOI:10.1007/s10270-020-00820-7