• International Journal of Contents
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• 제13권1호
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• pp.38-44
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• 2017

Increased use of software and complexity of software functions, as well as shortened software quality evaluation periods, have increased the importance and necessity for automation of software testing. Automating software testing by using machine learning not only minimizes errors in manual testing, but also allows a speedier evaluation. Research on machine learning in automated software testing has so far focused on solving special problems with algorithms, leading to difficulties for the software developers and testers, in applying machine learning to software testing automation. This paper, proposes a new machine learning framework for software testing automation through related studies. To maximize the performance of software testing, we analyzed and categorized the machine learning algorithms applicable to each software test phase, including the diverse data that can be used in the algorithms. We believe that our framework allows software developers or testers to choose a machine learning algorithm suitable for their purpose.

• Journal of Information Technology Applications and Management
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• 제12권2호
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• pp.1-13
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• 2005

This paper proposes a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase after developing it. The time-dependent behavior of testing effort expenditures is described by a Logistic curve. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied. SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull curve as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing-effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

• 대한임베디드공학회논문지
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• 제4권4호
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• pp.156-163
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• 2009

Recently a standard software platform for automotive, AUTOSAR, has been developed to manage growing software complexity and improve software reuseability. However reuse of testing system and test data are difficult because they are dependant on implementation language and testing phases. In this paper, we suggest a automated testing approach for AUTOSAR software component using a standardized testing language, TTCN-3. AUTOSAR defines the AUTOSAR XML Schema for the data exchange format so that it is possible to automatically convert AUTOSAR model into TTCN-3 testing model. Therefore our approach is to present generation techniques for the TTCN-3 testing system from a AUTOSAR XML description. With the proposed testing techniques we can reduce time and effort to build the testing system and reuse testing environment.

• 디지털융복합연구
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• 제11권3호
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• pp.293-298
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• 2013

소프트웨어 품질에 대한 중요성이 강조되어지고 있다. 개발에 주력하던 회사들도 소프트웨어 품질에 많은 관심을 가지고 있으며 품질을 개선하기 위한 노력을 기울이고 있다. 본 연구에서는 소프트웨어 테스팅을 통해서 얻어진 데이터를 분석하려 한다. 소프트웨어의 시험수와 시험에 소요된 날짜, 각 기능별 나타나는 발견된 오류수를 중심으로 소프트웨어 테스팅에 영향을 미치는 요인을 발견하려 한다. 또한 회귀분석을 통해서 소프트웨어 총 오류수에 가장 영향을 미치는 변인을 찾아보려 한다. 또한 테스터의 성별에 따라서 영향을 미치는 요인에 대한 분석을 하려 한다.

• 한국융합학회논문지
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• 제7권6호
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• pp.35-41
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• 2016

소프트웨어의 중요성이 높아지면서 소프트웨어 품질평가에 대한 관심이 높아지고 있다. 본 연구에서는 소프트웨어 품질 평가를 위한 국제 표준 문서를 비교 분석하고 테스트 데이터 분석을 통한 평가 방안을 제시한다. 국제표준 ISO/IEC 9126-2의 평가 모델과 ISO/IEC 25023의 평가 모델에 대한 차이점을 비교했다. ISO/IEC 25023의 평가모델인 8가지 품질 특성, 즉 기능성, 신뢰성, 사용성, 유지보수성, 이식성, 효율성, 상호운영성, 보안성적인 측면에서 평가 메트릭을 제시했다. 실제 테스트를 통해 얻어진 331개 자료를 분석해서 테스트 데이터의 발견된 오류 특징을 파악했다. 또한 결함 자료를 분석하고 차이점을 파악했다. 테스트데이터가 남녀에 따라서 시험 일수나 발견하는 품질 특성별 오류의 수에는 차이가 있음을 증명하고 시험일수를 기능성, 사용성, 성별을 가지고 예측했으며, 제품의 종류에 따라서도 오류수에 차이가 있음을 증명했다.

• 품질경영학회지
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• 제29권4호
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• pp.92-102
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• 2001

Software testing during development and operation should exercise to obtain the desired software quality and leave failure data set. So far, many software reliability models are classified and can be used to measure a software reliability only based on its failure history But, in practice, developers or testers of software systems must decide which existing software reliability model can be fitted. In this paper, we will show that an appropriate reliability model can be selected by considering relations between characteristics of each testing environment and models' assumptions. Several methods of software testing are presented and discussed. Also, unit test, integrated test, function test and system test that are sequentially exercised during development will be introduced.

• Nuclear Engineering and Technology
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• 제31권1호
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• pp.49-57
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• 1999

It has been a critical issue to predict the safety critical software reliability in nuclear engineering area. For many years, many researches have focused on the quantification of software reliability and there have been many models developed to quantify software reliability. Most software reliability models estimate the reliability with the failure data collected during the test assuming that the test environments well represent the operation profile. User's interest is however on the operational reliability rather than on the test reliability. The experiences show that the operational reliability is higher than the test reliability. With the assumption that the difference in reliability results from the change of environment, from testing to operation, testing environment factors comprising the aging factor and the coverage factor are developed in this paper and used to predict the ultimate operational reliability with the failure data in testing phase. It is by incorporating test environments applied beyond the operational profile into testing environment factors. The application results show that the proposed method can estimate the operational reliability accurately.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2005년도 춘계학술대회
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• pp.453-459
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• 2005

On this research, we show some concrete examples as software design, 2D/3D display, graph display, and gage display to develop a data monitoring system for real time safe fire testing. Developed software which is simulation software for live fire testing, has been designed to display informations about whole test status in a live fire testing, and with this, user can control a live fire testing under the safe environment. Beside, we increase a security by using a authority of user to access on this software. and we develop it based on module designed to apply a requirement of user later on.

• 대한안전경영과학회지
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• 제7권2호
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• pp.65-72
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• 2005

On this research, we show some concrete examples as software design, 2D/3D display, graph display, and gage display to develop a data monitoring system for real time safe fire testing. Developed software which is simulation software for live fire testing, has been designed to display informations about whole test status in a live fire testing, and with this, user can control a live fire testing under the safe environment. Beside, we increase a security by using a authority of user to access on this software. and we develop it based on module designed to apply a requirement of user later on.

• Journal of Information Technology Applications and Management
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• 제13권4호
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• pp.1-12
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• 2006

Many software reliability growth models(SRGM) have been proposed since the software reliability issue was raised in 1972. The technology to estimate and grow the reliability of developing S/W to target value during testing phase were developed using them. Most of these propositions assumed the S/W debugging testing efforts be constant or even did not consider them. A few papers were presented as the software reliability evaluation considering the testing effort was important afterwards. The testing effort forms which have been presented by this kind of papers were exponential, Rayleigh, Weibull, or logistic functions, and one of these 4 types was used as a testing effort function depending on the S/W developing circumstances. I propose the methology to evaluate the SRGM using least square estimator and maximum likelihood estimator for those 4 functions, and then examine parameters applying actual data adopted from real field test of developing S/W.