Modeling the Role of Testing Coverage in the Software Reliability Assessment
To assure the reliability and quality of the final product, testing is an essential and crucial part in the software development cycle. During this process, fault correction/detection activities are carried out to increase the reliability of the software. The non-homogeneous Poisson Process (NHPP) i...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Ram Arti Publishers
2023-06-01
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| Series: | International Journal of Mathematical, Engineering and Management Sciences |
| Subjects: | |
| Online Access: | https://www.ijmems.in/cms/storage/app/public/uploads/volumes/28-IJMEMS-22-0651-8-3-504-513-2023.pdf |
| _version_ | 1797850216946204672 |
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| author | Sudeep Kumar Anu G. Aggarwal Ritu Gupta |
| author_facet | Sudeep Kumar Anu G. Aggarwal Ritu Gupta |
| author_sort | Sudeep Kumar |
| collection | DOAJ |
| description | To assure the reliability and quality of the final product, testing is an essential and crucial part in the software development cycle. During this process, fault correction/detection activities are carried out to increase the reliability of the software. The non-homogeneous Poisson Process (NHPP) is the basis of the investigated software reliability growth models (SRGMs), which are based on the supposition that the number of faults found is affected by the amount of code covered during testing and that the amount of code covered during testing depends on the testing effort expended. This research takes into consideration several testing coverage functions: exponential, delayed S-shaped and logistic distributions, to propose three SRGMs that are based on testing efforts. For testing effort expenditure Weibull distribution has been employed. Two real failure datasets have been utilised to validate the proposed models, and their performance is evaluated using four goodness-of-fit metrics, including predictive ratio risk (PRR), coefficient of determination (R^2 ), predictive power (PP) and mean square error (MSE). Sensitivity analysis of cost requirement-based release time of software for exponential function has been done by using a genetic algorithm, which minimized the overall cost of the software subject to the requirement for reliability. |
| first_indexed | 2024-04-09T18:56:49Z |
| format | Article |
| id | doaj.art-23c7a42798ab4eb5ab7051559bd9bf3e |
| institution | Directory Open Access Journal |
| issn | 2455-7749 |
| language | English |
| last_indexed | 2024-04-09T18:56:49Z |
| publishDate | 2023-06-01 |
| publisher | Ram Arti Publishers |
| record_format | Article |
| series | International Journal of Mathematical, Engineering and Management Sciences |
| spelling | doaj.art-23c7a42798ab4eb5ab7051559bd9bf3e2023-04-09T10:51:15ZengRam Arti PublishersInternational Journal of Mathematical, Engineering and Management Sciences2455-77492023-06-0183504513https://doi.org/10.33889/IJMEMS.2023.8.3.028Modeling the Role of Testing Coverage in the Software Reliability AssessmentSudeep Kumar0Anu G. Aggarwal1Ritu Gupta2Department of Mathematics, AIAS, Amity University, Uttar Pradesh, 201303, India.Department of Operations Research, University of Delhi, Delhi, India.Department of Mathematics, AIAS, Amity University, Uttar Pradesh, 201303, India.To assure the reliability and quality of the final product, testing is an essential and crucial part in the software development cycle. During this process, fault correction/detection activities are carried out to increase the reliability of the software. The non-homogeneous Poisson Process (NHPP) is the basis of the investigated software reliability growth models (SRGMs), which are based on the supposition that the number of faults found is affected by the amount of code covered during testing and that the amount of code covered during testing depends on the testing effort expended. This research takes into consideration several testing coverage functions: exponential, delayed S-shaped and logistic distributions, to propose three SRGMs that are based on testing efforts. For testing effort expenditure Weibull distribution has been employed. Two real failure datasets have been utilised to validate the proposed models, and their performance is evaluated using four goodness-of-fit metrics, including predictive ratio risk (PRR), coefficient of determination (R^2 ), predictive power (PP) and mean square error (MSE). Sensitivity analysis of cost requirement-based release time of software for exponential function has been done by using a genetic algorithm, which minimized the overall cost of the software subject to the requirement for reliability. https://www.ijmems.in/cms/storage/app/public/uploads/volumes/28-IJMEMS-22-0651-8-3-504-513-2023.pdftesting coveragesoftware reliability growth modelsnon-homogeneous poisson processsoftware reliabilityrelease planningtesting effort |
| spellingShingle | Sudeep Kumar Anu G. Aggarwal Ritu Gupta Modeling the Role of Testing Coverage in the Software Reliability Assessment International Journal of Mathematical, Engineering and Management Sciences testing coverage software reliability growth models non-homogeneous poisson process software reliability release planning testing effort |
| title | Modeling the Role of Testing Coverage in the Software Reliability Assessment |
| title_full | Modeling the Role of Testing Coverage in the Software Reliability Assessment |
| title_fullStr | Modeling the Role of Testing Coverage in the Software Reliability Assessment |
| title_full_unstemmed | Modeling the Role of Testing Coverage in the Software Reliability Assessment |
| title_short | Modeling the Role of Testing Coverage in the Software Reliability Assessment |
| title_sort | modeling the role of testing coverage in the software reliability assessment |
| topic | testing coverage software reliability growth models non-homogeneous poisson process software reliability release planning testing effort |
| url | https://www.ijmems.in/cms/storage/app/public/uploads/volumes/28-IJMEMS-22-0651-8-3-504-513-2023.pdf |
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