Journal of KIISE (정보과학회 논문지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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A Method to Establish Severity Weight of Defect Factors for Application Software using ANP

ANP 모형을 이용한 응용 소프트웨어 결함요소에 대한 중요도 가중치 설정 기법

  • 허상무 (서울과학기술대학교 IT정책전문대학원 산업정보시스템) ;
  • 김우제 (서울과학기술대학교 글로벌융합산업공학과)
  • Received : 2015.03.24
  • Accepted : 2015.09.11
  • Published : 2015.11.15
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Abstract

In order to improve software quality, it is necessary to efficiently and effectively remove software defects in source codes. In the development field, defects are removed according to removal ratio or severity of defects. There are several studies on the removal of defects based on software quality attributes, and several other studies have been done to improve the software quality using classification of the severity of defects, when working on projects. These studies have thus far been insufficient in terms of identifying if there exists relationships between defects or whether any type of defect is more important than others. Therefore, in this study, we collected various types of software defects, standards organization, companies, and researchers. We modeled the defects types using an ANP model, and developed the weighted severities of the defects types, with respect to the general application software, using the ANP model. When general application software is developed, we will be able to use the weight for each severity of defect type, and we expect to be able to remove defects efficiently and effectively.

소프트웨어 품질을 향상하기 위해서는 소스에 내재된 결함을 효율적, 효과적으로 제거해야 한다. 개발현장에서는 결함 심각도와 결함 제거율로 결함을 제거하고 있다. 결함을 이용하여 품질을 향상하기 위한 연구로는 결함 발생 빈도과 ISO 품질속성을 이용하여 품질을 향상하려는 연구가 있고, 프로젝트 수행 시 결함을 심각도로 관리하여 품질을 향상시키는 연구가 있었다. 하지만, 결함 자체에 집중하여 결함을 유형화하여 결함 유형 간에는 어떤 영향력이 있는지, 그 영향력으로 인하여 어느 결함 유형이 더 중요한 지에 대한 연구는 미흡한 실정이었다. 이에 본 연구에서는 표준단체, 업체, 연구자들의 소프트웨어 결함 유형을 수집, 분류하여 ANP로 모형화하였다. 또한, 구성된 ANP 모형을 이용하여 일반 응용 소프트웨어에 대하여 결함 유형별 중요도 가중치를 산정하였다. 일반 응용 소프트웨어를 개발할 때, 산정된 가중치를 적용하여 결함을 제거한다면, 좀 더 효율적이고 효과적으로 소프트웨어 품질을 향상할 수 있으리라 기대한다.

Keywords

Acknowledgement

Supported by : 서울과학기술대학교

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