Optimal test activity allocation for covariate software reliability and security models

Nagaraju, Vidhyashree; Jayasinghe, Chathuri L.; Fiondella, Lance

doi:10.1016/j.jss.2020.110643

Cited by 15 publications

(6 citation statements)

References 14 publications

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“…Following notations are used in the calculation of CRITIC method. Resource allocation modeling during testing phase under dynamic environment Anand et al 9 Optimal allocation of testing resources Nagarju et al 10 Introduced NHPP model that integrates covariates dependent on the relative hazards model of the discrete Cox.…”

Section: Critic Approachmentioning

confidence: 99%

“…TA B L E 4 Data set (DS1) of weekly radio access control system for wireless networks [45][46][47] However, Euclidean distance from positive ideal solution (𝑆 + 𝑚 ) and negative ideal solution (𝑆 − 𝑚 ) for each alternative is calculated by using Equations ( 9) and (10), respectively. The calculated results are shown in Table 13 for data set 1.…”

Section: Numerical Illustrationmentioning

confidence: 99%

“…Furthermore, Table 22 Ideal best value (𝑉 + ) and Ideal worst value (𝑉 − )of each ranking criteria for data set 2 is calculated by using Equations ( 7) and ( 8), respectively. Table 23 represents Euclidean distance from positive ideal solution (𝑆 + 𝑚 ) and negative ideal solution (𝑆 − 𝑚 ) for each alternative that is calculated by using Equations ( 9) and (10), respectively. Lastly, as shown in Table 23, the relative closeness (𝑡 𝑚 )of each possible SRGM is determined using Equation (11).…”

Section: Timementioning

confidence: 99%

“…discussed the optimal allocation of test resources for two versions considering the multiup gradation phenomenon. Nagarju et al 10 . introduced a reliability growth model of nonhomogeneous Poisson process (NHPP) software that integrates covariates dependent on the relative discrete Cox hazard model.…”

Section: Literature Reviewmentioning

confidence: 99%

“…10 introduced a reliability growth model of nonhomogeneous Poisson process (NHPP) software that integrates covariates dependent on the relative discrete Cox hazard model. Kapur et al11 developed a model using Shannon entropy to quantify the complexity in the source code.…”

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confidence: 99%

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A novel CRITIC‐TOPSIS approach for optimal selection of software reliability growth model (SRGM)

Saxena

Kumar

Ram

2022

Quality & Reliability Eng

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Various Software Reliability Growth Models (SRGMs) have been developed over last five decades to estimate the failure rate, software reliability and remaining number of faults in the software during testing phase of software development life cycle. There are numerous SRGMs available in the research literature and in the presence of numerous SRGM, appropriate selection is a staggering task for the software testing professionals. In the software reliability area, researchers have always been interested to select the optimal SRGM to use in a particular situation. In this study, we have developed an integrated technique based on Criteria Importance Through Inter Criteria Correlation (CRITIC) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to select the optimal SRGM. The weights of criteria are obtained by the CRITIC method and SRGMs are ranked by order using TOPSIS method. The working of proposed integrated CRITIC‐TOPSIS approach is illustrated on the two real‐time failure data sets. Furthermore, the methodology validation idea supports the current study by comparing the results obtained with the previous multi‐criteria decision making (MCDM) methodologies namely Additive Ratio Assessment (ARAS). The study revealed that the ranking of SRGMs can be solved effectively using the integration of CRITIC and TOPSIS. The result of this study plays a significant role to take decisions and to evaluate the feasibility of SRGM.

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Section: Critic Approachmentioning

confidence: 99%