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1.3. Original Contribution

1.3    Original Contribution

The following results are considered to be the original contribution of this thesis:

1.    Introduction and formalization of the General Business Logic Model - the formal description of the BPMN process model and its integration with rules are presented in Sections 4.3 and 4.4 in Chapter 4.

2.    Definition of the SKE-specific Business Logic Model - Generality of the introduced General Business Logic Model allows for its application to specific approaches. Thus, a BPMN process model is in-tegrated with the SKE approach as the SKE-specific Business Business Logic Model, presented in Section 5.3 in Chapter 5.

3.    Extension of formalization ofthe Attribute Relationship Diagram method - in order to support formal description of the translation algorithm, the improved formalization of the ARD model from the SKE approach is introduced in Section 6.1 in Chapter 6.

4.    Definition of the translation from an ARD model into an SKE-specific Business Logic Model - the algorithm for automatic generation of Business Process models from ARD models along with an exemplary translation is presented in Sections 6.2 and 6.3 in Chapter 6.

5.    Providing the modę ling and execution environment for the integrated approach - models that are a re-sult of the proposed translation are supported by the modeling and execution environment presented in Section 7.2 in Chapter 7.

1.4    Exclusions

As Business Process Management constitutes a wide research area [242], this thesis is focused on modeling and executing of Business Process models with rules. Therefore neighbour aspects related to selecting model from collections (like merging models or configuring models) [36], monitoring and adapting pro-cesses [140], analyzing models (verifying, conformance checking) [240, 7, 58, 208], improving models using e.g. simulation [6, 67] are not significant in this context and are not discussed as related works.

Moreover, the dissertation also omits the broad process mining field as process mining techniąues are based on event data [241] and the approach presented in the thesis is based on data model prepared for the specific domain and not related to the observed behavior from logs.

The work described in this dissertation is supported by the “Methodology for designing Hierarchical Business Processes integrated with Business Rules” (HiBuProBuRul) research project funded from NCN (National Science Center) resources for science according to decision no. DEC-2011/03/N/ST6/00909¹.

'See: http://geist.agh.edu.pl/pub:projects:hibuproburul:start.

K. Kluza Methods for Modeling and Integration of Business Processes with Rules