Shortening the Cycle of Software Reliability Testing with Fuzzy Discrimination

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.

[1]  Minyan Lu,et al.  Software reliability accelerated testing method based on mixed testing , 2010, 2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS).

[2]  John D. Musa,et al.  Operational profiles in software-reliability engineering , 1993, IEEE Software.

[3]  Ruan Lian.  Usage Profile Construction Technique for Generation of Software Reliability Test Data , 2006 .

[4]  Chen Huo.  Software Statistical Test Acceleration Based on Importance Sampling , 2005 .

[5]  Tadashi Dohi,et al.  A Software Accelerated Life Testing Model , 2010, 2010 IEEE 16th Pacific Rim International Symposium on Dependable Computing.

[6]  Tsong Yueh Chen,et al.  Mirror adaptive random testing , 2004, Inf. Softw. Technol..

[7]  Jun Ai,et al.  Automatic verification environment for embedded software reliability testing , 2011, The Proceedings of 2011 9th International Conference on Reliability, Maintainability and Safety.

[8]  James Miller,et al.  A Novel Evolutionary Approach for Adaptive Random Testing , 2009, IEEE Transactions on Reliability.

[9]  Bojan Cukic,et al.  Accelerated Testing for Software Reliability Assessment , 2007 .

[10]  Tsong Yueh Chen,et al.  Quasi-Random Testing , 2005, IEEE Transactions on Reliability.

[11]  Ruan Lian.  Generation of Reliability Test Data for Real-Time Embedded Software , 2007 .

[12]  Jian Wang,et al.  Study on the accelerated software reliability demonstration testing for high reliability software based on strengthened operational profile , 2010, 2010 2nd International Conference on Computer Technology and Development.

[13]  Jun Zheng,et al.  Software reliability accelerated testing based on the combined testing method , 2011, The Proceedings of 2011 9th International Conference on Reliability, Maintainability and Safety.

[14]  L.J. Gullo,et al.  Accelerated stress testing to detect probabilistic software failures , 2004, Annual Symposium Reliability and Maintainability, 2004 - RAMS.

[15]  Huai Liu,et al.  Application of a Failure Driven Test Profile in Random Testing , 2009, IEEE Trans. Reliab..