Publicação
Derivation of data-driven software models from business process representations
| Resumo: | Organizations are constantly being challenged with new demands imposed by markets and have to respond to new requirements imposed by governments. Organizations need to be prepared to face those challenges and demands in order to survive. Business Process Management (BPM) allows organizations to know themselves and to be prepared to ght new challenges and easily adapt to new situations. BPM is being seen as a key for innovation helping in the simulation of possible scenarios. For these and other reasons, business process management and modeling is being increasingly used by organizations. A business process model usually is created under the supervision, clari - cation, approval and validation of the business stakeholders. Thus, a business process model is a proper representation of the reality, having lots of useful information that can be used in the development of the software system that will support the business. Several authors proposed approaches to derive software models based on business process models. Nevertheless, the generation of a data model based on business process models has been constantly ignored mostly because business process models did not support, until recently, the identi cation of the persistent data. However, interest in the data and its preservation have increased in the BPMN (Business Process Model and Notation) most recent version, which allows identifying the persistent data manipulated within business processes. This research work presents and discusses two approaches to derive a data model from business process models: directly, by piecing together information from a set of business process models; and indirectly, by adapting the 4SRS (Four Step Rule Set) method to generate a logical software architecture from business process models and extending it to derive the data model from the logical software architecture. The direct approach is suitable to deal with complete business process models, whereas the indirect approach is more suitable to deal with complex systems, being prepared to detect incomplete business process models and to complete the information derived from business process models with information from other sources. The derived data model will serve as a basis for the software development, helping reducing time and e orts spent in software design, ensuring the alignment between the software and the business processes, and enabling traceability between the elements in software models and the corresponding business process models. |
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| Autores principais: | Cruz, Estrela |
| Assunto: | Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| Ano: | 2016 |
| País: | Portugal |
| Tipo de documento: | tese de doutoramento |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | Organizations are constantly being challenged with new demands imposed by markets and have to respond to new requirements imposed by governments. Organizations need to be prepared to face those challenges and demands in order to survive. Business Process Management (BPM) allows organizations to know themselves and to be prepared to ght new challenges and easily adapt to new situations. BPM is being seen as a key for innovation helping in the simulation of possible scenarios. For these and other reasons, business process management and modeling is being increasingly used by organizations. A business process model usually is created under the supervision, clari - cation, approval and validation of the business stakeholders. Thus, a business process model is a proper representation of the reality, having lots of useful information that can be used in the development of the software system that will support the business. Several authors proposed approaches to derive software models based on business process models. Nevertheless, the generation of a data model based on business process models has been constantly ignored mostly because business process models did not support, until recently, the identi cation of the persistent data. However, interest in the data and its preservation have increased in the BPMN (Business Process Model and Notation) most recent version, which allows identifying the persistent data manipulated within business processes. This research work presents and discusses two approaches to derive a data model from business process models: directly, by piecing together information from a set of business process models; and indirectly, by adapting the 4SRS (Four Step Rule Set) method to generate a logical software architecture from business process models and extending it to derive the data model from the logical software architecture. The direct approach is suitable to deal with complete business process models, whereas the indirect approach is more suitable to deal with complex systems, being prepared to detect incomplete business process models and to complete the information derived from business process models with information from other sources. The derived data model will serve as a basis for the software development, helping reducing time and e orts spent in software design, ensuring the alignment between the software and the business processes, and enabling traceability between the elements in software models and the corresponding business process models. |
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