• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.57-66
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• 2007

Organizations of Software development are very important issue on enhancement of a software quality as rapid progress of software industry. Especially there are diverse attempts for enhancement of test maturity of the software organization through some kinds of the test maturity model. But the current test maturity models based on CMM(Capability Maturity Model) lack part of actual testing measurement and only measure level of test maturity. To solve these problems, we suggest 'double V-model' to execute both software development process and test process simultaneously, and also 'test attributes to Maturity Levels Correlation Matrix' for evaluating level of test maturity included with definitions of test attribute and level. That is, we enhance TMM(Test Maturity Model) adopted with 'Improvement Suggestion' of TPI(Test Process Improvement) which is easy the evaluation of test maturity of organization and gives the direction of improvement to level up the test maturity for the measured organization. As a result, we will contribute to level up the test maturity of the organization.

• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.487-489
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• 2004

소프트웨어 테스트는 소프트웨어 개발 과정에 매우 중요한 요소이다. 현재 많은 조직들이 테스트 성숙도를 높이기 위한 노력을 진행하고 있다. 그 중에서 일리노이공대의 TMM(Test Maturity Model)이 대표적이라고 볼 수 있다. 하지만 TMM은 바로 테스트 성숙수준을 측정하는데 문제가 있다. 그래서 TMM과 테스트 프로세스를 향상시킬 수 있는 TPI(Test Process Improvement) 모델을 통해, 우리는 Enhanced-TMM에 테스트 속성과 성숙도 상호관련 매트릭스를 사용한 테스트 성숙수준 측정 방법을 구체적으로 제안하고자 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.307-309
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• 2005

빠른 산업 발전 속에서 조직과 시스템이 복잡하고 대형화되면서 소프트웨어 품질을 향상시키고 그들의 신뢰성을 측정하기 위한 성숙도 모델들이 개발되었다. 그 중에서도 CMM와 이를 발전시킨 CMMI는 많은 조직에서 적용하기 위해 노력을 기울이고 있다. 하지만 두 모델들은 테스트 속성과 테스트 프로세스에 대한 언급이 부족하다. 본 논문에서는 모든 영역을 고려한 새로운 모델을 만들기 보다는 테스트 중심으로 개발된 TMM을 사용하여 CMMI과의 매핑을 통해 소프트웨어 조직의 생산품질과 신뢰성을 향상 시키는 방법을 제안한다. 논문에서는 CMMI 단점과 이를 보완하는 방법을 제안하고 이를 위해 TMM과 CMMI의 매핑전략에 언급한다. 이를 통해 기대되는 효과를 제시한다.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.8
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• pp.379-384
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• 2017

In real software business environment, there are required to validate software quality in diverse usage range of software for many small & medium companies. Software quality means both qualities of production and process. In our situation, we focus on better process quality of a test organization than a whole organization. But even the original test maturity model (TMM) does not enough to apply with our domestic venture/small & medium companies. To solve this problem, we suggest the simplified test maturity model for our companies. We redefine this simplified model with the original TMM and a test process improvement next (TPI next) model. The previous models just have provided each definition of maturity level, goal and activity per each level, which not exists an assessment guideline and a formal assessing procedure. Due to this reasons, an assessor is difficult to assess the test organization without them. this paper suggest an assessment guideline of the simplified TMM and also define the procedure which is included with activities and byproducts. With these assessment guideline, an assessor can work possible to formally assess test organizations of small & medium companies, and with self assessment guideline they can be correctly provision before assessment of their organizations.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.270-278
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• 2022

This study was conducted using deep learning technology to classify for 'Mihwang' peach maturity with RGB images and fruit quality attributes during fruit development and maturation periods. The 730 images of peach were used in the training data set and validation data set at a ratio of 8:2. The remains of 170 images were used to test the deep learning models. In this study, among the fruit quality attributes, firmness, Hue value, and a^* value were adapted to the index with maturity classification, such as immature, mature, and over mature fruit. This study used the CNN (Convolutional Neural Networks) models for image classification; VGG16 and InceptionV3 of GoogLeNet. The performance results show 87.1% and 83.6% with Hue left value in VGG16 and InceptionV3, respectively. In contrast, the performance results show 72.2% and 76.9% with firmness in VGG16 and InceptionV3, respectively. The loss rate shows 54.3% and 62.1% with firmness in VGG16 and InceptionV3, respectively. It considers increasing for adapting a field utilization with firmness index in peach.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.15-20
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• 2022

This research studied the evaluation of reliability among the software quality characteristics: suitability, reliability, usability, portability, maintainability, performance efficiency, security, and compatibility. It proposes a quantitative evaluation of reliability in the measurement of software quality. This study introduces a method for measuring the failure rate included in maturity during reliability evaluation, which is one of the characteristics of software quality, and is a study with experimental data on how the failure rate changes depending on the form of failure data. Focusing on software testing, the failure rate was measured and compared according to the type of failure data by applying it to the software reliability growth model, focusing on the number of failures per day. The failure rate was measured around the failure time found through the 6-day test, and the failure rate was compared with the failure rate proposed by the international standard ISO/IEC 25023 using the measurement results, and the application was reviewed according to the data type.