Sequential Sampling Designs for Estimating Software Reliability

For any non-trivial system, it is impossible to reach the exact reliability of software due to the complexity, cost, and time required to complete the testing. Instead, a sample of test cases can be used to estimate the overall software reliability. Our objective is to obtain the most accurate estimate of software reliability by allocating test cases among partitions. In the traditional approach, the method of allocating test cases among partitions is determined before reliability testing begins. By allocating test cases in advance, there is no opportunity to take advantage of the errors in choosing the distributions of test cases that may occur during the testing of the software. The inability to use these errors to adjust the estimate during testing is a shortcoming of a fixed sampling scheme. We applied sequential sampling schemes to make allocation decisions dynamically throughout the testing process. Under these sampling schemes, we can refine the allocation of test cases sequentially based on the information gained as the testing proceeds. Using theoretical results and Monte Carlo simulation, we have shown that the proposed sequential sampling scheme performs at least as well as the balanced sampling scheme.

Name thesis:degree_name

Ph.D. (Doctor of Philosophy)

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Mathematics (UMKC)

Grantor

University of Missouri--Kansas City

Year dc:date.issued

2020

Author dc:creator

• Alanazi, Bader

Advisors dc:contributor.advisor

• Rekab, Kamel
• Rulis, Paul Michael, 1976-

Handle dc:identifier.uri

https://hdl.handle.net/10355/75786

OAI identifier oai:identifier

oai:mospace.umsystem.edu:10355/75786