Software reliability growth model for testing‐domain

Ohtera, Hiroshi; Yamada, Shigeru; Narihisa, Hiroyuki

doi:10.1002/scj.4690220203

Cited by 3 publications

(5 citation statements)

References 6 publications

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“…Figure 7 shows the time-dependent behavior of the testing domain growth function γ(t) in Eq. (6). It represents the rate of increase of detectable faults at an arbitrary testing time t. From Fig.…”

Section: Discussion Of the Estimation Resultsmentioning

confidence: 99%

“…Clearly, in the case of β = 0 in Eq. (4), we have the following equation as the basic testing domain function [6]:…”

Section: The Testing Domain Functionmentioning

confidence: 99%

“…Thus, there is a set of testing paths of modules and functions in the software system that are influenced by the test cases. This set of testing paths is called a testing domain [6]. The isolated testing domain ratio has a close relation to the quantity of test cases run.…”

Section: Introductionmentioning

confidence: 99%

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A testing‐domain‐dependent software reliability growth model for imperfect debugging environment and its evaluation of goodness‐of‐fit

Fujiwara

Yamada

2002

Electron Comm Jpn Pt III

Self Cite

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SUMMARYMany software reliability growth models which reflect various testing environments in the software development and operation/maintenance environment as a method for attaining a highly reliable software system have been proposed. These models assume a perfect debugging environment. That is, the detected faults are assumed to be corrected and removed certainly without introducing new faults. If we describe the software fault-detection phenomenon more exactly, it is realistic to assume that new faults can be introduced by the debugging activities. In this paper, we propose a software reliability growth model based on the testing domain in the software system, which is isolated by the executed test cases in software testing. In particular, our model assumes an imperfect debugging environment in which new faults are introduced in the fault-correction process, and is formulated as a nonhomogeneous Poisson process. Further, it is applied to fault-detection data observed in actual development projects, the results of software reliability assessment are shown, and comparisons of goodness-of-fit with the existing software reliability growth model are performed.

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Section: Discussion Of the Estimation Resultsmentioning

confidence: 99%

“…Clearly, in the case of β = 0 in Eq. (4), we have the following equation as the basic testing domain function [6]:…”

Section: The Testing Domain Functionmentioning

confidence: 99%

See 1 more Smart Citation

A testing‐domain‐dependent software reliability growth model for imperfect debugging environment and its evaluation of goodness‐of‐fit

Fujiwara

Yamada

2002

Electron Comm Jpn Pt III

Self Cite

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“…Some of them based on Non-Homogenous Poisson Process (NHPP) models are proposed to predict the future failures (Anand et al, 2016). "In the testing phase of software development, there is a set of modules and functions in a software system to be influenced by executed cases (Othera et al, 1990). The test cases executed on the software in the testing phase are developed to influence the faults lying dormant in various modules/functions implemented in the software based on the requirement specifications.…”

Section: Introductionmentioning

confidence: 99%

Testing Domain Dependent Software Reliability Growth Models

Deepika¹,

Singh²,

Anand³

et al. 2017

Int J Math, Eng, Manag Sci

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Software Reliability Growth Models (SRGMs) are supporting software industries in expecting and scrutinizing quality of software. Numerous SRGMs have been proposed; majority of which concentrate on testing period of software. For testing, domain specific knowledge plays a very crucial role. Based on necessity condition, a set of programmes are in testing phase of software development. “Domain testing is a software technique in which small number of test cases is selected for trial. These sets of testing paths, all of which are to be eventually influenced by designed test cases are called the testing domain which expands with the progress of testing”. Keeping this concept in mind, we propose SRGMs with the concept of testing domain with exponential coverage. Utility of proposed framework has been emphasized in this paper through some models pertaining to different distribution i.e Exponential, Logistic, Weibull and Rayleigh. Moreover, the data analysis is performed to find the estimates of parameters by fitting the models on authentic data sets.

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“…This set is called the testing-domain [4]. The isolated testing-domain ratio in the software system is closely related to the quality and quantity of executed test-cases.…”

Section: Introductionmentioning

confidence: 99%