• Proceedings of the Korean Reliability Society Conference
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• 2004.07a
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• pp.73-117
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• 2004

Software 기술의 변화: 다중프로그래밍, 다중 사용자(multiuser), 실시간처리/데이터베이스, 제품소프트웨어 출현, 강력한 데스크-탑 시스템, 객체지향 시스템, 전문가 시스템, 인공지능(중략)

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.251-257
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• 2005

Software system which is essential in operating the computer has gradually become an indispensable element in many aspects of our daily lives and an important factor in numerous systems. In recent years, software cost sometimes exceeds the cost of maintaining the hardware system. In addition to the cost necessary to develop the new software system and to maintain the system, the penalty costs incurred due to software failures are even more significant. In this paper, a cost model incorporating the warranty cost, debugging costto remove each fault detected in the software system, and delivery delay cost is developed. A software reliability model based on non-homogeneous Poisson process(NHPP) is established and the optimal software release policies to minimize the expected total software cost are discussed. Numerical examples are provided to illustrate the results.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.199-207
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• 2001

The failure rate functions between successive failures are of concatenated form. We allow the parameters of failure rate function change after a certain failure and its fixing. We confine out attention to a model wherein the interfailure times are described by its failure rate function. We suggest an adaptive failure rate function with a change-point under the assumption that interfailure times are record value statistics from a Weibull distribution. The proposed model will be applied through a practical example of software failure data.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.815-823
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• 2012

In this paper reliability growth model in which the operating time between successive failure is a continuous random variable is proposed. This model is for Burr type XII distribution with two parameters which is discussed in two versions: the order statistics and non-homogeneous Poisson process. The two software reliability measures are obtained. The performance for two versions of the suggested model is tested on real data set by U-plot and Y-plot using Kolmogorov distance.

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.259-264
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• 2005

In this paper, we generalize the software reliability growth model by assuming that the testing cost and maintenance cost are random and adopts the Bayesian approach to determine the optimal software release time. Numerical examples are provided to illustrate the Bayesian method for certain parametric models.

• Proceedings of the CALSEC Conference
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• 2002.01a
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• pp.479-483
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• 2002

Research Purpose Present a Reliability Measurement Model for e-biz solutions in J2ee environment Address problems with software reliability of e-biz solutions To remove defects as early as possible in the development process Reduce or eliminate defects from software-improve software quality(omitted)

• Journal of Korean Society for Quality Management
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• v.19 no.1
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• pp.65-71
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• 1991

According to characters of software, the methods of evaluating reliability are different. The purpose of this study was to develop application software used in the field and to set up reliability model which failure density was used so that in the process of test, developer and user may apply a point of time to field business and to apply developed model which real data use used.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.835-842
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• 2001

We propose a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase. The time-dependent behavior of testing effort expenditures is described by a Weibull 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, we discuss the relations between testing time and reliability and between duration following failure fixing and reliability are studied in this paper. The release time making the testing cost to be minimum is determined through studying the cost for each condition. Also, the release time is determined depending on the conditions of the specified reliability. The optimum release time is determined by simultaneously studying optimum release time issue that determines both the cost related time and the specified reliability related time.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.7
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• pp.265-274
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• 2019

The reliability test performed when developing the weapon system software is classified into static test and dynamic test. In static test, checking the coding rules, vulnerabilities and source code metric are performed without executing the software. In dynamic test, its functions are verified by executing the actual software based on requirements and the code coverage is measured. The purpose of this static/dynamic test is to find out defects that exist in the software. However, there still exist defects that can't be detected only by the current reliability test on the weapon system software. In this paper, whether defects that may occur in the software can be detected by static test and dynamic test of the current reliability test on the weapon system is analyzed through experiments. As a result, we provide guidance on improving the reliability test of weapon system software, especially the dynamic test.

• Journal of KIISE
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• v.42 no.12
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• pp.1551-1560
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• 2015

Software Reliability Growth Models (SRGMs) are used to quantitatively evaluate software reliability and to determine the software release date or additional testing efforts using software failure data. Because a single SRGM is not universally applicable to all kinds of software, the selection of an optimal SRGM suitable to a specific case has been an important issue. The existing methods for SRGM selection assess the goodness-of-fit of the SRGM in terms of the collected failure data but do not consider the accuracy of future failure predictions. In this paper, we propose a method for selecting SRGMs using the trend of failure data and failure prediction ability. To justify our approach, we identify problems associated with the existing SRGM selection methods through experiments and show that our method for selecting SRGMs is superior to the existing methods with respect to the accuracy of future failure prediction.