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Managing Consistency of Business Process Models across Abstraction Levels

Process models support the transition from business requirements to IT
implementations. An organization that adopts process modeling often maintain
several co-existing models of the same business process. These models target different
abstraction levels and stakeholder perspectives. Maintaining consistency among
these models has become a major challenge for such an organization. For
instance, propagating changes requires identifying tacit correspondences among the models,
which may be only in the memories of their original creators or may be lost
entirely.

Although different tools target specific needs of different roles,
we lack appropriate support for checking whether related models
maintained by different groups of specialists are still consistent after independent
editing. As a result, typical consistency management tasks such as
tracing, differencing, comparing, refactoring, merging, conformance checking,
change notification, and versioning are frequently done manually, which is
time-consuming and error-prone.

This thesis presents the Shared Model, a framework designed to improve
support for consistency management and impact analysis in process modeling. The
framework is designed as a result of a comprehensive industrial study that
elicited typical correspondence patterns between Business and IT process models
and the meaning of consistency between them.

The framework encompasses three major techniques and contributions:
1) matching heuristics to automatically discover complex correspondences
patterns among the models, and to maintain traceability among model
parts---elements and fragments; 2) a generator of edit operations to compute the
difference between process models; 3) a process model synchronizer, capable of
consistently propagating changes made to any model to its counterpart.

We evaluated the Shared Model experimentally. The evaluation shows that the
framework can consistently synchronize Business and IT views related by
correspondence patterns, after non-simultaneous independent editing.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OWTU.10012/8310
Date January 2014
CreatorsALMEIDA CASTELO BRANCO, MOISES
ContributorsCZARNECKI, KRZYSZTOF
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeThesis or Dissertation

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