• Title/Summary/Keyword: 소프트웨어 메트릭

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A Comparative Experiment of Software Defect Prediction Models using Object Oriented Metrics (객체지향 메트릭을 이용한 결함 예측 모형의 실험적 비교)

  • Kim, Yun-Kyu;Kim, Tae-Yeon;Chae, Heung-Seok
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.8
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    • pp.596-600
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    • 2009
  • To support an efficient management of software verification and validation activities, many defect prediction models have been proposed based on object oriented metrics. They usually adopt logistic regression analysis, And, they state that the correctness of prediction is about 60${\sim}$70%, We performed a similar experiment with Eclipse 3.3 to check their prediction effectiveness, However, the result shows that correctness is about 40% which is much lower than the original results. We also found that univariate logistic regression analysis produces better results than multivariate logistic regression analysis.

Definition of Security Metrics for Software Security-enhanced Development (소프트웨어 개발보안 활동을 위한 보안메트릭 정의)

  • Seo, Dongsu
    • Journal of Internet Computing and Services
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    • v.17 no.4
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    • pp.79-86
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    • 2016
  • Under the influence of software security-enhanced development guidelines announced in 2012, secure coding practices become widely applicable in developing information systems aiming to enhance security capabilities. Although continuous enhancement activities for code security is important, management issues for code security have been less addressed in the guidelines. This paper analyses limitation of secure coding practices from the viewpoint of quality management. In particular this paper suggests structures and the use of software metrics from coding to maintenance phases so that it can be of help in the future by extending the use of security metrics.

Taxonomy Framework for Metric-based Software Quality Prediction Models (소프트웨어 품질 예측 모델을 위한 분류 프레임워크)

  • Hong, Euy-Seok
    • The Journal of the Korea Contents Association
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    • v.10 no.6
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    • pp.134-143
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    • 2010
  • This paper proposes a framework for classifying metric-based software quality prediction models, especially case of software criticality, into four types. Models are classified along two vectors: input metric forms and the necessity of past project data. Each type has its own characteristics and its strength and weakness are compared with those of other types using newly defined criteria. Through this qualitative evaluation each organization can choose a proper model to suit its environment. My earlier studies of criticality prediction model implemented specific models in each type and evaluated their prediction performances. In this paper I analyze the experimental results and show that the characteristics of a model type is the another key of successful model selection.

Software Quality Prediction based on Defect Severity (결함 심각도에 기반한 소프트웨어 품질 예측)

  • Hong, Euy-Seok
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.5
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    • pp.73-81
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    • 2015
  • Most of the software fault prediction studies focused on the binary classification model that predicts whether an input entity has faults or not. However the ability to predict entity fault-proneness in various severity categories is more useful because not all faults have the same severity. In this paper, we propose fault prediction models at different severity levels of faults using traditional size and complexity metrics. They are ternary classification models and use four machine learning algorithms for their training. Empirical analysis is performed using two NASA public data sets and a performance measure, accuracy. The evaluation results show that backpropagation neural network model outperforms other models on both data sets, with about 81% and 88% in terms of accuracy score respectively.

Extraction of Data Quality Characteristics from Dirty Data (데이터 오류에서 추출한 데이터 품질 특성)

  • 김수경;최병주
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.04a
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    • pp.549-551
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    • 2000
  • 소프트웨어 제품의 품질을 보증하는 일은 매우 중요하며, 국제표준인 ISO/IEC 9126은 소프트웨어 품질 및 특성 및 측정 메트릭 표준을 제공하고 있다. 이때 ISO/IEC 9126에서는 소프트웨어를 프로그램, 절차, 규칙 및 관련문서로 한정하고 있기 때문에 데이터의 품질에는 적용할 수 없다. 본 논문에서는 데이터 품질 평가 및 제어를 위하여 데이터 오류 형태를 분류하고, 이를 기반으로 데이트 품질 특성 및 부특성을 분류한다. 데이터 품질 특성 분류는 ISO/IEC 9126에 정의한 소프트웨어 품질 특성을 데이터 오류 형태에 대응시켜 추출한다. 본 논문에서 제시하는 데이트 품질특성 분류는 지식 공학(knowledge engineering)시스템이 최종 사용자에게 제공하는 데이터나 지식의 품질 측정 및 제어에 기준이 된다.

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A Study on Quality Characteristics of SW Measurement for Embedded System (임베디드 시스템 소프트웨어 측정을 위한 품질 특성 연구)

  • 오광근;김태환;문전일;임계영;김진태;박수용
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10b
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    • pp.385-387
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    • 2003
  • 하드웨어 비중이 큰 임베디드 시스템 특성상, 하드웨어 중심적인 품질 측정 및 평가가 이루어져 왔으나, 소프트웨어 규모 증가로 인해 임베디드 시스템에서도 소프트웨어 품질에 대한 체계적인 관리의 필요성이 대두 되고 있다. 이에 본 연구에서는 임베디드 시스템 소프트웨어 측정을 위한 품질 특성을 조사 하였으며, LG산전 인버터 시스템에 대한 품질 메트릭 추출을 통해 임베디드 시스템 제품의 품질 측정 가능성을 확인하였다.

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Design ad Implementation of Quality Evaluation Toolkit for FMS Software (FMS 소프트웨어에 대한 품질평가 툴킷의 설계 및 구현)

  • 양해술;이하용
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10a
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    • pp.572-574
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    • 1999
  • 공장자동화는 최근 급격히 발전하고 있는 분야로서 부가가치가 매우 높은 산업에 속한다. 공장자동화는 자동화를 구성하는 기계장치뿐만 아니라 기계의 전반적인 운영을 담당하는 소프트웨어 또한 큰 비중을 차지하고 있다. 결국, 공장자동화를 통해 생산되는 제품의 품질은 기계 장치의 정밀도, 견고성 등의 측면과 함께 운영 소프트웨어의 품질로부터 받는 영향도 무시할 수 없다. 본 연구 과제에서는 공장자동화 소프트웨어의 한 유형인 FMS (Flexible Manufacturing System)나 Cell Controller를 중심으로 품질평가를 수행할 수 있는 평가 메트릭과 방법을 개발하고 이를 적용하여 효율적인 평가를 수행할 수 있는 툴킷의 프로토타입을 설계하고 구현하였다.

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Hybrid metrics model to predict fault-proneness of large software systems (대형 소프트웨어 시스템의 결함경향성 예측을 위한 혼성 메트릭 모델)

  • Hong, Euy-Seok
    • The Journal of Korean Association of Computer Education
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    • v.8 no.5
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    • pp.129-137
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    • 2005
  • Criticality prediction models that identify fault-prone spots using system design specifications play an important role in reducing development costs of large systems such as telecommunication systems. Many criticality prediction models using complexity metrics have been suggested. But most of them need training data set for model training. And they are classification models that can only classify design entities into fault-prone group and non fault-prone group. To solve this problem, this paper builds a new prediction model, HMM, using two styled hybrid metrics. HMM has strong point that it does not need training data and it enables comparison between design entities by criticality. HMM is implemented and compared with a well-known prediction model, BackPropagation neural network Model(BPM), considering internal characteristics and accuracy of prediction.

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Quality Evaluation for the Usability of Multimedia Web Sites (멀티미디어 웹 사이트 사용성 품질 평가)

  • Min, Jang-Geun;Lee, Keum-Suk
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.5 s.43
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    • pp.139-148
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    • 2006
  • This study is intended to propose quality criteria and Web metrics for usability quality evaluation of multimedia Web sites. Recently, applications of the Web sites are not limited to the area of industry and operating as it integrates the new technology. Also as information super highway becomes common with development or network technology, multimedia Web site is on the rise due to various use of multimedia attributes. Therefore this study expands to apply HTML based Web site quality evaluation studied in Software engineering, HCI, Hypermedia to multimedia Web site, and suggests new metrics by integrating flash usability which is expanding its portion in multimedia Web site lately. The Web metrics proposed in this study are verified by heuristic evaluation from a group of expert. It analyses the results of quantitative and qualitative qualify evaluation on Web Award Korea by comparing the award-winning, high-quality Web site with non-winning Web sites. This study can be used to establish guideline for high-quality multimedia Web site development in the future.

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Guideline for Test Process Improvement of Test Organization Through Correlating TMMi with TPI NEXT (상관관계를 통한 조직의 테스트 프로세스 개선 가이드 방안)

  • Kim, Kidu;Park, Young Bom;Kim, R. Youngchul
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.12
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    • pp.823-828
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    • 2013
  • In this paper, it will improve in quality to adapt a right test process which is formalized from certification of TMMi Level. To do this, we suggest correlative relation through analyzing associations between TMMi and TPI next based on the previous research[10], which provides the guideline for enhancing test process level with measuring Test maturity model. Also schematize test maturity measurement through refining and improving the previous test maturity correlation metrics[6,8,9]. As one example with limited level, it shows the guideline to improve test process of one testing organization through improved correlation metrics with TMMi and TPI next.