Flexible software reliability growth model with testing effort dependent learning process

Kapur, P. K.; Goswami, Debkalpa; Bardhan, Amit Kumar; Singh, Ompal

doi:10.1016/j.apm.2007.04.002

Cited by 74 publications

(34 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Early researches related SRGM with respect to testing time [3,17]. However, incorporation of testing resources leads to development of more accurate SRGMs [4,5,9,26]. The reason being, the detection of faults are more intimately linked to the amount of resources expended [18,24] on testing as it includes-(a) Manpower, that takes into account  Testing group (malfunction recognition personnel).…”

Section: 'Bmentioning

confidence: 99%

“…They established that both exponential-type and S-type NHPP models can come under ideal and imperfect debugging situations. Later, Kapur et al [9] deliberated on the testing resource reliant learning process and classified faults into two types on the source of amount of testing resources needed to remove them. This paper models fault exclusion rate in terms of testing resource.…”

Section:  Debugging Group (Programmers\failure Rectification Personnmentioning

confidence: 99%

See 1 more Smart Citation

A study of Optimal Testing Resource Allocation Problem for Modular Software with Change Point

Kaur

Aggarwal

Kedia³

2018

Proceedings of the First International Conference on Information Technology and Knowledge Management

View full text Add to dashboard Cite

Abstract-For evolving trustworthy software, engrossing on uncovering process of fault in software is central. Nevertheless, during testing, modifications in the testing routine, defect gravity or testing-skill maturity and working environment, there can be notable change in fault detection rate. When this sort of pattern is observed in testing time it is called change point. In this article, we inquire a resource distribution problem that optimally distributes software developing resources in such a way that the cost of development is curtailed to optimization. In this problem, for all modules the effect of chief circumstantial element of change-point is considered. The constraint of pulling off the desired reliability level for every individual module is also incorporated in the formulation of the problem. A framework based on Karush Kuhn Tucker (KKT) conditions is presented to work out the resulting non-linear optimization problem. A simulated numerical illustration has been analyzed to reflect the formulation of the case and its solution by the algorithm proposed.

show abstract

Section: 'Bmentioning

confidence: 99%

Section:  Debugging Group (Programmers\failure Rectification Personnmentioning

confidence: 99%

A study of Optimal Testing Resource Allocation Problem for Modular Software with Change Point

Kaur

Aggarwal

Kedia³

2018

Proceedings of the First International Conference on Information Technology and Knowledge Management

View full text Add to dashboard Cite

show abstract

“…The effort based SRGMs proposed in the past use exponential, Rayleigh, logistic, or Weibull distributions to specify testing effort function (TEF) to denote effort consumption during testing [11][12][13]. Although these functions seem to give good result and can well fit in some cases, there is a fallacy in assuming finite total test effort at an infinite time.…”

Section: Introductionmentioning

confidence: 99%

“…Some SRGMs have been proposed with testing effort function (TEF) [11][12][13], since the fault detection and correction depend on efforts consumed such as test cases executed, man-days expended, computer utilization time, and other resources consumed, rather than only testing time or calendar time. The effort based SRGMs proposed in the past use exponential, Rayleigh, logistic, or Weibull distributions to specify testing effort function (TEF) to denote effort consumption during testing [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

“…Many such SRGMs have been proposed as parametric [1][2][3][4][5][6][7][8][9][10][11][12][13][14] and nonparametric [15][16][17][18] models since the year 1972 to estimate future failure occurrence times and assess the reliability growth of software systems during the testing phase. The traditional SRGMs are based on the premise that the mean value function of the model follows either exponential growth [1,3] or S-shaped growth [2,11] or both [4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Machine Learning Approach for Software Reliability Growth Modeling with Infinite Testing Effort Function

Ramasamy

Lakshmanan

2017

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Reliability is one of the quantifiable software quality attributes. Software Reliability Growth Models (SRGMs) are used to assess the reliability achieved at different times of testing. Traditional time-based SRGMs may not be accurate enough in all situations where test effort varies with time. To overcome this lacuna, test effort was used instead of time in SRGMs. In the past, finite test effort functions were proposed, which may not be realistic as, at infinite testing time, test effort will be infinite. Hence in this paper, we propose an infinite test effort function in conjunction with a classical Nonhomogeneous Poisson Process (NHPP) model. We use Artificial Neural Network (ANN) for training the proposed model with software failure data. Here it is possible to get a large set of weights for the same model to describe the past failure data equally well. We use machine learning approach to select the appropriate set of weights for the model which will describe both the past and the future data well. We compare the performance of the proposed model with existing model using practical software failure data sets. The proposed log-power TEF based SRGM describes all types of failure data equally well and also improves the accuracy of parameter estimation more than existing TEF and can be used for software release time determination as well.

show abstract

Suitability analysis of software reliability models for its applicability on NPP systems

Kumar

Singh

Kumar

2018

Quality & Reliability Eng

View full text Add to dashboard Cite

The advent of software components in the safety critical systems of nuclear power plant has introduced new challenges for software professionals to provide increased software reliability. Several proposals have been proposed for ensuring software reliability in different phases of software development life cycle. The present article is a novel attempt in providing an exhaustive survey of software reliability models for their applicability on safety critical systems of nuclear power plants. Our systematic review shows that none of the proposals for ensuring software reliability are applicable on such systems. The issues and challenges are discussed, and a software reliability model for safety critical system of nuclear power plants is proposed.

show abstract

Flexible software reliability growth model with testing effort dependent learning process

Cited by 74 publications

References 11 publications

A study of Optimal Testing Resource Allocation Problem for Modular Software with Change Point

A study of Optimal Testing Resource Allocation Problem for Modular Software with Change Point

Machine Learning Approach for Software Reliability Growth Modeling with Infinite Testing Effort Function

Suitability analysis of software reliability models for its applicability on NPP systems

Contact Info

Product

Resources

About