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Variability Dependency Analysis for Generating Business Process Models based on Variability Decisions

가변성 결정기반 BPM 생성을 위한 가변성 의존관계 분석

  • 문미경 (동서대학교 컴퓨터정보공학부)
  • Published : 2009.10.31

Abstract

Recently, the business process family model (BPFM), which is new approachfor assuring businessflexibility and enhancing reuse in application development with service oriented architecture (SOA), was proposed. The BPFM is a model which can explicitly represent the variabilities in business process family by using the variability analysis method of software product line. Many business process models (BPM) can be generated automatically through decision and pruning processes from BPFM. At this time, the variabilities tend to have inclusive or exclusive dependencies between them. This affects the decision and pruning processes. So far, little attention has been given to the binding information of variability dependency in the BPFM. In this paper, we propose an approach for analyzing various types of dependency relationships between variabilities and representing the variability and their relationships as a dependency analysis model. Additionally, a method which can trace the variabilities affected by a decision on the dependency analysis model is presented. The case study shows that the proposed approach helps to reduce the number of variability decision and to solve a disagreement of functions in BPM produced by incorrectly deciding the variability.

최근 서비스 지향 아키텍처 (Service Oriented Architecture SOA) 기반의 애플리케이션 개발에 맞게 비즈니스 프로세스의 유연성을 확보하고 재사용을 증진시키기 위하여 비즈니스 프로세스 패밀리 모델 (Business Process Family Model: BPFM)이 제시되었다. BPFM은 소프트웨어 프로덕트 라인 방법의 가변성 분석 기법을 사용하여 비즈니스 프로세스 군 (family)에서 나타날 수 있는 가변성을 분석하여 이를 명시적으로 표현하고 있는 모델이다. BPFM으로부터 여러 개의 비즈니스 프로세스 모델 (Business Process Model: BPM)을 개발하기 위해서는 가변성 결정 및 가지치기(Decision and Pruning) 과정을 거쳐야 한다. 이 때 가변성 사이에는 서로 협력적 또는 배타적인 관계를 가질 수 있고 이는 가변성 결정과 가지치기에 영향을 미치게 되는데, 현재 제시된 BPFM에는 이러한 바인딩 정보에 대해서 고려하지 않고 있다. 본 논문에서는 비즈니스 프로세스 군에서 식별될 수 있는 가변성들 사이의 의존관계 유형을 분석하고 이러한 가변성 정보를 독립된 의존관계 분석모델로 표현하는 방법을 제시한다. 또한 추출된 모델을 기반으로 하나의 가변성 결정으로부터 영향을 받는 다른 가변성들을 추적하여 선결정 처리 할 수 있는 방법을 제공한다. 본 방법을 이용함으로써 가변성 결정회수를 줄일 수 있고, 또한 잘못된 가변성 결정으로 인한 BPM의 기능 불일치를 해소할 수 있음을 사례연구를 통해 보인다.

Keywords

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