• Journal of Advanced Marine Engineering and Technology
• /
• v.25 no.5
• /
• pp.1058-1064
• /
• 2001

In this paper, the development of probability distribution estimation program for fatigue crack growth lives was summarize. The probability distribution estimation program of life was developed to increase the reliability of life estimation. In this study, it is considered that the cause of scatter in fatigue crack growth data is due to material inhomogeneity. The material resistance to fatigue crack growth is modelled as a spatial stochastic process, which varies randomly along the crack path. We developed the GUI program to estimate the probability distribution and reliability using the non-Gaussian stochastic process method. This program can be used for the reliability assessment.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.35C no.5
• /
• pp.11-16
• /
• 1998

We analyze the software reliability growth models for the specified period from the viewpoint of theory of differential equations. we defien a genralized form of reliability growth models as follws: dN(t)/dt = b(t)f(N(t)), Where N(t) is the number of remaining faults and b(t) is the failure rate per software fault at time t. We show that the well-known three software reliability growth models - Goel - Okumoto, s-shaped, and Musa-Okumoto model- are special cases of the generalized form. We, also, extend the generalized form into an extended form being dN(t)/dt = b(t, .gamma.)f(N(t)), The genneralized form can be obtained if the distribution of failures is given. The extended form can be used to describe a software reliabilit growth model having weibull density function as a fault exposure rate. As an application of the generalized form, we classify three mentioned models according to the forms of b(t) and f(N(t)). Also, we present a case study applying the generalized form.

• Communications for Statistical Applications and Methods
• /
• v.18 no.5
• /
• pp.667-674
• /
• 2011

A recent trend in software reliability engineering accounts for the coverage growth behavior during testing. The coverage growth function (representing the coverage growth behavior) has become an essential component of software reliability models. Application of a coverage growth function requires the estimation of the coverage growth function. This paper considers the problem of estimating the coverage growth function. The existing maximum likelihood method is reviewed and corrected. A method of minimizing the sum of squares of the standardized prediction error is proposed for situations where the maximum likelihood method is not applicable.

• Journal of Korean Society for Quality Management
• /
• v.23 no.3
• /
• pp.57-68
• /
• 1995

In this paper, we consider possibility that the multiple errors occur in each testing stage. At present, software reliability modeling is considered as a part of software reliability quality assurance in software engineering. However they dealt with the software growth model for the single error debugging at each testing stage until now. Hence it is necessary to study software reliability with multiple errors debugging. Therefore we propose software reliability growth modeling and estimate the parameters in the proposed software reliability growth model for the multiple errors debugging at each testing stage.

• Journal of applied mathematics & informatics
• /
• v.9 no.2
• /
• pp.761-769
• /
• 2002

Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed. The testing time on the right is truncated in this model. The instantaneous failure rate, mean-value function, error detection rate, reliability of the software, estimation of parameters and the simple applications of this model are discussed .

• Communications for Statistical Applications and Methods
• /
• v.14 no.3
• /
• pp.497-506
• /
• 2007

Coverage-based NHPP SRGMs have been introduced in order to incorporate the coverage growth behavior into the NHPP SRGMs. The coverage growth function representing the coverage growth behavior during testing is thus an essential factor of the coverage-based NHPP SRGMs. This paper proposes a class of discrete time coverage growth functions and illustrates its application to real data sets.

• The KIPS Transactions:PartD
• /
• v.10D no.5
• /
• pp.829-836
• /
• 2003

Software Reliability Growth Model that have been studied variously. But measurement of correct parameter of this model is not easy. Specially, estimation of correct model about failure data must be establish and estimation of parameter can consist exactly. To get correct testing, we calculate the normal score and describe the normal probability plot. Use the normal probability plot, we estimate the distribution for failure data. In this paper, we estimate the software reliability growth model for through the normal probability plot. In this research, we applies software reliability growth model through distribution characteristics of failure data. If we see plot, we determine the software reliability growth model, we can make sure superior in model's performance estimation.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.7
• /
• pp.406-418
• /
• 2020

When developing weapons systems, it is important to implement the functions and performance of equipment suitable for development purposes, but it is very important to ensure that the equipment is capable of operating without any vacuum with reliability after development. Therefore, various activities are carried out to enhance reliability of equipment. Reliability is enhanced by using high-specification parts in development, reliability verification through analysis, and testing using development prototypes to reinforce and improve the parts that are lacking in equipment. However, recently, development schedules are shortened due to rapidly changing external conditions and technologies, and there are cases where sufficient reliability growth activities were not carried out due to problems such as cost. Examples are projects that perform reliability activities only in analytical methods (reliability, FMECA). In this paper, analyzing and testing methods for analysis and testing were carried out on the same equipment through FMECA and super-accelerated life test, the contents of reliability growth activity were derived, the results of design change/review were accordingly compared, the differences between the two methods were analyzed, and measures were proposed to strengthen reliable growth activities. It was concluded that reliable growth activities through analysis from the beginning of development and reliable growth activities through testing should be carried out at the completion of initial prototype production.

• Journal of the Korea Computer Industry Society
• /
• v.3 no.7
• /
• pp.837-844
• /
• 2002

In general, software test is carried out to detect or repair errors in system during software development process. Namely, we can evaluate software reliability through collecting and removing the faults detected in testing phase. Software reliability growth model evaluates reliability of software mathematically. Many kinds of software reliability growth modeling which modeling the processes of detecting, revising and removing the faults detected in testing phase have been proposed in many ways. and, it is assumed that almost of these modeling have one typed detect and show the uniformed detection rate. In this study, significance levels of the faults detected in test phase are classified according to how they can affect on the whole system and then the fault detection capability of them is applied. From this point of view, We here by propose a software reliability growth model with faults detection capability according considering fault significance levels and apply some fault data to this proposed model and finally verify its validity by comparing and estimating with the existing modeling.

• The KIPS Transactions:PartD
• /
• v.11D no.6
• /
• pp.1287-1294
• /
• 2004

Recently relationships between reliability measures and the coverage have been developed for evaluation of software reliability. Particularly the mean value function of the coverage-based software reliability growth model is important because of its key role in rep-resenting the software reliability growth. In this paper, we first review the problems of the existing mean value functions with respect to the assumptions on which they are based. Then a new mean value function is proposed. The new mean value function is developed for a general testing environment in which imperfect fault detection and repeated construct execution are allowed. Finally performance of the proposed model is empirically evaluated by applying it to a real data set.