Hee-Cheul Kim ¹

Affiliations
1 Department of Industrial and Management Engineering, Namseoul University, KR

Abstract

Software testing in the debugging process is more efficient if it knows, in advance, to reduce costs in terms of changes in the software reliability and testing costs. In this process, essential items for software development are the reliability, cost, and consideration of release time. In this paper, the software reliability growth cost model based on Non-Homogenous Poisson Process (NHPP) about the property of learning effect for delayed software s-shaped reliability model was proposed, that was considered the actual number of faults removed in the software operation period after release time. Then discuss the relationship between release time and software testing-effort for determine the optimal release time so that can minimize the cost of software development and get more profit. Finally, according to some empirical studies, directly explain the effect of different parameters about the optimal software release time during testing process.

Keywords

Learning Effect, NHPP, Software Cost Model, S-Shaped Reliability Model

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Kyung-Soo Kim ¹, Hee-Cheul Kim ²

Affiliations
1 Department of Internet Information, Baek Seok Culturel University, KR
2 Department of Industrial and Management Engineering, Namseoul University, KR

Abstract

Objectives: In the procedure of the developing software product, the software administrators are needed to have tools/ mechanisms to detect software failures. In this research, the test implements with perspective about actual learning effects were considered based on the software reliability models. Methods/Statistical Analysis: The log-linear pattern as the lifetime distribution was offered using the finite failure NHPP. Software error detection techniques contain self-directed errors-noticed element and learning element. These two elements can be discussed from the influencing elements. When applied to log-linear property model, the learning element was more efficient than the self-directed errors-noticed element model. Findings: When applied to log-linear property model, the learning element was more efficient than the self-directed errors-noticed element model. The examination of a failure time data considering the influencing elements was achieved using software failure interval time and the maximum likelihood estimation was used for parameter estimation. Besides, the competence of the data from the trend analysis was established. And, the model choice was skilled using MSE and R2. The reliability considering the influential elements for each model is showing a decrease pattern. In terms of reliability, the greater learning element has revealed the low reliability. In terms of judgment of the reliability, a case of the reliability for the assumed mission time, the self-directed errors-noticed element than the learning element model has shown the lower reliability. Namely, the cases of the learning element are greater or equal greater than self-directed errors-noticed element shows propensity to rise slightly, but a property of the reliability shows tend to rise progressively have the decreasing pattern for the mission time. Eventually, the reliability has sensitive property for the learning element about the mission time. Improvements/Applications: The software testing for the debugging to reduce cost in terms of the reliability from software is an essential problem. From a research, the software developers must be considered for the growth model by the prior knowledge of the software to identify failure modes which can be able to help.

Keywords

Learning Effects, Log-linear Distribution, Mission Time, Non-Homogeneous Poisson Process, Trend Analysis.

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Hee-Cheul Kim ¹

Affiliations
1 Department of Industrial and Management Engineering, Namseoul University, KR

Abstract

Background/Objectives: In this research, the comparative problems of a reliability model about Lomax and Gomperz distribution property were proposed. The maximum likelihood estimation and bisection method were used to the parameter estimation. Methods/Statistical Analysis: As special occasions, the model selection based on the Mean Square Error and coefficient of determination for the efficient model was conducted. Analysis of a failure time using real data set from the proposing reliability model (based on Lomax and Gomperz distribution) was worked. To obtain for the data reliability, the Laplace trend test was employed. Findings: In this study, the proposed Lomax than Gomperz distribution model is more efficient model in this area. The case of the higher shaping parameter of the Lomax distribution model is judged more reliable model in this field. Thus, Lomax distribution model can also be applied as a special model. Improvements: The software testing for the debugging to reduce cost in terms of the reliability from software is essential problem. From a research, the software developers must be considered for the growth model by the prior knowledge of the software to identify failure modes which can be able to help.

Keywords

Gomperz Distribution, Laplace Trend Test, Lomax Distribution, Mission Time, NHPP.

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