Multi-release software model based on testing coverage incorporating random effect (SDE)
In the past, various Software Reliability Growth Models (SRGMs) have been proposed using different parameters to improve software worthiness. Testing Coverage is one such parameter that has been studied in numerous models of software in the past and it has proved its influence on the reliability mod...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-01-01
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| Series: | MethodsX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215016123000791 |
| _version_ | 1797796436274839552 |
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| author | Ritu Bibyan Sameer Anand Anu G. Aggarwal Gurjeet Kaur |
| author_facet | Ritu Bibyan Sameer Anand Anu G. Aggarwal Gurjeet Kaur |
| author_sort | Ritu Bibyan |
| collection | DOAJ |
| description | In the past, various Software Reliability Growth Models (SRGMs) have been proposed using different parameters to improve software worthiness. Testing Coverage is one such parameter that has been studied in numerous models of software in the past and it has proved its influence on the reliability models. To sustain themselves in the market, software firms keep upgrading their software with new features or enhancements by rectifying previously reported faults. Also, there is an impact of the random effect on testing coverage during both the testing and operational phase. In this paper, we have proposed a Software reliability growth model based on testing coverage with random effect along with imperfect debugging. Later, the multi-release problem is presented for the proposed model. The proposed model is validated on the dataset from Tandem Computers. The results for each release of the models have been discussed based on the different performance criteria. The numerical results illustrate that models fit the failure data significantly. • The random effect in the testing coverage rate is handled using Stochastic Differential Equations (SDE). • Three testing coverage functions used are Exponential, Weibull, and S-shaped. • Four Releases of the software model has been presented. |
| first_indexed | 2024-03-13T03:33:03Z |
| format | Article |
| id | doaj.art-0ebb1d86ab714c7a9c332c96683b8efd |
| institution | Directory Open Access Journal |
| issn | 2215-0161 |
| language | English |
| last_indexed | 2024-03-13T03:33:03Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | MethodsX |
| spelling | doaj.art-0ebb1d86ab714c7a9c332c96683b8efd2023-06-24T05:17:14ZengElsevierMethodsX2215-01612023-01-0110102076Multi-release software model based on testing coverage incorporating random effect (SDE)Ritu Bibyan0Sameer Anand1Anu G. Aggarwal2Gurjeet Kaur3Department of Operational Research, University of Delhi, New Delhi, IndiaShaheed Sukhdev College of Business Studies, University of Delhi, New Delhi, India; Corresponding author.Department of Operational Research, University of Delhi, New Delhi, IndiaDepartment of Operational Research, University of Delhi, New Delhi, IndiaIn the past, various Software Reliability Growth Models (SRGMs) have been proposed using different parameters to improve software worthiness. Testing Coverage is one such parameter that has been studied in numerous models of software in the past and it has proved its influence on the reliability models. To sustain themselves in the market, software firms keep upgrading their software with new features or enhancements by rectifying previously reported faults. Also, there is an impact of the random effect on testing coverage during both the testing and operational phase. In this paper, we have proposed a Software reliability growth model based on testing coverage with random effect along with imperfect debugging. Later, the multi-release problem is presented for the proposed model. The proposed model is validated on the dataset from Tandem Computers. The results for each release of the models have been discussed based on the different performance criteria. The numerical results illustrate that models fit the failure data significantly. • The random effect in the testing coverage rate is handled using Stochastic Differential Equations (SDE). • Three testing coverage functions used are Exponential, Weibull, and S-shaped. • Four Releases of the software model has been presented.http://www.sciencedirect.com/science/article/pii/S2215016123000791Testing Coverage incorporating SDE with Multi Release SRGM |
| spellingShingle | Ritu Bibyan Sameer Anand Anu G. Aggarwal Gurjeet Kaur Multi-release software model based on testing coverage incorporating random effect (SDE) MethodsX Testing Coverage incorporating SDE with Multi Release SRGM |
| title | Multi-release software model based on testing coverage incorporating random effect (SDE) |
| title_full | Multi-release software model based on testing coverage incorporating random effect (SDE) |
| title_fullStr | Multi-release software model based on testing coverage incorporating random effect (SDE) |
| title_full_unstemmed | Multi-release software model based on testing coverage incorporating random effect (SDE) |
| title_short | Multi-release software model based on testing coverage incorporating random effect (SDE) |
| title_sort | multi release software model based on testing coverage incorporating random effect sde |
| topic | Testing Coverage incorporating SDE with Multi Release SRGM |
| url | http://www.sciencedirect.com/science/article/pii/S2215016123000791 |
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