Shortening the Cycle of Software Reliability Testing with Fuzzy Discrimination

Abstract

Software reliability testing (SRT) is random testing based on the operational profile that acquires failure data to estimate the reliability of a software product in quantifiable terms. A huge number of test cases with lengthy execution periods are currently required to satisfy the probability distribution of the operational profile and the actual usage situation. These test cases lead to a long execution cycle time of the SRT, a primary reason for the difficulties in applying SRT widely in engineering science today. In this paper, fuzzy discrimination is adopted to analyze the similarities among the test cases generated by random samples based on the operational profile. A similarity level introduced by the fuzzy discrimination indicates the similarity among the test cases. Specifically, if the similarity level is more than the confidence level λ, which is defined before the testing, the test case can be skipped and the probable testing execution time is recorded. With more test cases joining the fuzzy discrimination, more test cases can be skipped and test execution times will decrease, thus increasing both the efficiency and the applicability of SRT. Once testing is completed, the time between the failures is acquired, and a software reliability assessment can be realized without changing the assessment models of software reliability.