Volume 7 Number 9 (Sep. 2012)
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JSW 2012 Vol.7(9): 2061-2068 ISSN: 1796-217X
doi: 10.4304/jsw.7.9.2061-2068

Software Reliability Test Based on Markov Usage Model

Kuanjiu Zhou, Xiaolong Wang, Gang Hou1, Jie Wang, and Shanbin Ai
School of Software, Dalian University of Technology, Dalian, China

Abstract—The reliability test for embedded software system is very difficult due to its complex structure and large scale. Markov usage model which describes the software usage with Markov process is widely used for statistical test. Software statistical test based on Markov usage model is an effective approach to the generation of test cases with high efficiency and the evaluation of software reliability in a quantitative way. This paper mainly focuses on the generation of Markov usage model of software system and the method of software reliability test based on it. Firstly, a method to build Markov usage model based on improved state transition matrix (STM), which is a table-based modeling language, is proposed. Then a software reliability test method including test case generation and test adequacy determination based on Markov usage model is presented. An improved Kullback discriminant is selected as the judgment criteria of convergence from the test chain to the usage chain in order to measure whether the testing process is sufficient. Finally, a Markov test cases generation tool MTCG is developed which implements the methods put forward in this paper. Experimental verification of test adequacy and efficiency is made through a comparison between the Markov usage model-based method and a completely random test method, the results of which show that software reliability test based on Markov usage model is approving, high-efficient and promising.

Index Terms—Markov Usage Model, Software Reliability Test, Test Case Generation, Test Adequacy

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Cite: Kuanjiu Zhou, Xiaolong Wang, Gang Hou1, Jie Wang, and Shanbin Ai, "Software Reliability Test Based on Markov Usage Model," Journal of Software vol. 7, no. 9, pp. 2061-2068, 2012.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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