Prognosing the compliance of declarative business processes using event trace robustness

María Teresa Gómez-López, Luisa Parody, Rafael M. Gasca, Stefanie Rinderle-Ma

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations


Several proposals have studied the compliance of execution of business process traces in accordance with a set of compliance rules. Unfortunately, the detection of a compliance violation (diagnosis) means that the observed events have already violated the compliance rules that describe the model. In turn, the detection of a compliance violation before its actual occurrence would prevent misbehavior of the business processes. This functionality is referred to as proactive management of compliance violations in literature. However, existing approaches focus on the detection of inconsistencies between the compliance rules or monitoring process instances that are in a violable state. The notion of robustness could help us to prognosticate the occurrence of these inconsistent states in a premature way, and to detect, depending on the current execution state of the process instance, how “close” the execution is to a possible violation. On top of being able to possibly avoid violations, a robust trace is not sensitive to small changes. In this paper we propose the way to determine whether a process instance is robust against a set of compliance rules during its execution at runtime. Thanks to the use of constraint programming and the capacities of super solutions, a robust trace can be guaranteed.

Original languageEnglish
Title of host publicationOn the Move to Meaningful Internet Systems
Subtitle of host publicationOTM 2014 Conferences - Confederated International Conferences: CoopIS and ODBASE 2014, Proceedings
EditorsRobert Meersman, Hervé Panetto, Tharam Dillon, Michele Missikoff, Lin Liu, Oscar Pastor, Alfredo Cuzzocrea, Timos Sellis
PublisherSpringer Verlag
Number of pages18
ISBN (Electronic)9783662455623
StatePublished - 2014
Externally publishedYes
EventInternational Conferences: CoopIS and ODBASE 2014 - Amantea, Italy
Duration: 27 Oct 201431 Oct 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Conferences: CoopIS and ODBASE 2014


  • Compliance Rules
  • Declarative Business Process
  • Model-based Prognosis
  • Robustness


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