• Journal of Applied Reliability
• /
• v.1 no.2
• /
• pp.175-181
• /
• 2001

Recently, the quality of software has become a major issue. The statistical models used in making predictions about the quality of software are termed software reliability growth models (SRGM). However, the existing SRGMs have not been satisfactory in predicting software reliability behavior (Keiller and Miller(1991), Keiller and Littlewood(1984), Musa(1987)). In this paper, we present a fuzzy-based interval estimation of software errors (failures).

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.7
• /
• pp.2076-2085
• /
• 2000

Almost all existing software reliability models are based on the assumptions of he software usage and software failure process. There, therefore, is no universally applicable software reliability model. To develop a universal software reliability model this paper suggests the predictive filter as a general software reliability prediction model for time domain failure data. Its usefulness is empirically verified by analyzing the failure datasets obtained from 14 different software projects. Based on the average relative prediction error, the suggested predictive filter is compared with other well-known neural network models and statistical software reliability growth models. Experimental results show that the predictive filter generally results in a simple model and adapts well across different software projects.

• Journal of the Korea Convergence Society
• /
• v.10 no.3
• /
• pp.59-65
• /
• 2019

In this paper, we propose a software quality measurement metrics of ISO / IEC 25023, which is newly proposed for software quality evaluation, to compare the difference with ISO / IEC 9126-2 which was used for software quality evaluation. In this paper, we propose a method for evaluating the quality of reliability based on the software reliability growth model among the eight quality characteristics presented in ISO / IEC 25023. Based on ISO / IEC 25023, software-quality evaluations demonstrate that there is some risk in evaluating reliability when based on data.

• Journal of the Korean Data and Information Science Society
• /
• v.19 no.4
• /
• pp.1361-1369
• /
• 2008

The analysis of software reliability model provides the means to analysts, software engineers, and systems analysts and developers who want to predict, estimate, and measure failure rate of occurrences in software. In this paper, reliability growth model, in which the operating time between successive failure is a continuous random variable, is proposed. This model is based on order statistics of two parameters Burr type XII distribution. We propose the measure based on U-plot. Also the performance of the suggested model is tested on real data set.

• Journal of Korean Institute of Industrial Engineers
• /
• v.30 no.4
• /
• pp.261-266
• /
• 2004

In this paper, the software reliability growth model which incorporates the periodic maintenance after the release is proposed. Using the proposed model, the debugging and periodic maintenance cost subject to the required level of the software reliability are investigated. An optimal software release time is derived for a fixed interval of periodic maintenance. To validate the proposed model, release times obtained in this study are compared with examples. The proposed investigation is expected to be served as one of factors in determining the release time of the software where periodic maintenance is considered.

• Communications for Statistical Applications and Methods
• /
• v.12 no.3
• /
• pp.673-682
• /
• 2005

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

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.4A
• /
• pp.399-414
• /
• 2004

In this paper, an evolution of software reliability engineering in a large-scale software project is summarized. The considered software consists of many components, called functional blocks in software of switching system. These functional blocks are served as the unit of coding and test, and the software is continuously updated by adding new functional blocks. We are mainly concerned with the analysis of the effects of these software components in software reliability and reliability evolution. We analyze the static characteristics of the software related to software reliability using collected failure data during system test. We also discussed a pattern which represents a local and global growth of the software reliability as version evolves. To find the pattern of system software, we apply the S-shaped model to a collection of failure data sets of each evolutionary version and the Goel-Okumoto(G-O) model to a grouped overall failure data set. We expect this pattern analysis will be helpful to plan and manage necessary human/resources fur a new similar software project which is developed under the same developing circumstances by estimating the total software failures with respect to its size and time.

• Convergence Security Journal
• /
• v.12 no.1
• /
• pp.9-16
• /
• 2012

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 for testing time. The testing time on the right is truncated in this model. The intensity function, mean-value function, reliability of the software, estimation of parameters and the special applications of Pareto NHPP model are discussed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection, depended on difference between predictions and actual values, were efficient using the mean square error and $R_{SQ}$.

• Communications for Statistical Applications and Methods
• /
• v.15 no.6
• /
• pp.875-881
• /
• 2008

This paper first discusses the existing non-homogeneous Poisson process(NHPP) software reliability growth model(SRGM) frameworks with respect to capability of representing software reliability growth phenomenon. As an enhancement of representational capability a new general coverage-based NHPP SRGM framework is developed. Issues associated with application of the new framework are then considered.

• The KIPS Transactions:PartD
• /
• v.8D no.4
• /
• pp.409-420
• /
• 2001

Recently a new approach to evaluation of software reliability, one of important attributes of a software system, during testing has been devised. This approach utilizes test coverage information. The coverage-based software reliability growth models recently appeared in the literature are first reviewed and classified into two classes. Inherent problems of each of the two classes are then discussed and their validity is empirically investigated. In addition, a new mean value function in coverage and a heuristic procedure for selecting the best coverage are proposed.