ISCAS OpenIR
Enhancing software reliability estimates using modified adaptive testing
Hu, Hai (1); Jiang, Chang-Hai (1); Cai, Kai-Yuan (1); Wong, W. Eric (3); Mathur, Aditya P. (4); Hu, H.(huhai.orion@gmail.com)
2013
Pages288-300
Indexed TypeSCI ; EI
Publish PlaceElsevier, P.O. Box 211, Amsterdam, 1000 AE, Netherlands
ISSN9505849
Department(1) Department of Automatic Control, Beijing University of Aeronautics and Astronautics, Beijing 100191, China; (2) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China; (3) Department of Computer Science, University of Texas at Dallas, United States; (4) Department of Computer Science, Purdue University, United States
English AbstractContext: Most software reliability models are based on a binary notion of correctness, i.e. "successful" or "failed." However, in several instances, it is important to account of failure severity to obtain more descriptive and accurate estimates of the reliability of the software. Objective: In this paper, we develop a set of extended metrics based on the Nelson's software reliability model to account for information gained from a user's point of view regarding the severity of the observed failures. Model formulation based on multi-granularity failure severity is provided, and the proposed metrics are proved to be backward compatible. Method: In order to estimate the software reliability through testing, an extended adaptive testing strategy, namely Modified Adaptive Testing (MAT) is proposed. The use of test history information allows the resulting test process to be adaptive in the selection of tests under limited test budget. Simulations and experiments on real-life programs are conducted to evaluate the effectiveness of MAT. Results: Data show that the reliability estimates obtained using MAT (a) are closer to the "true" reliability than those obtained using random testing and (b) lead to lower variance than the techniques used for comparison, which means MAT can be applied to help testers and reliability engineers better understand the reliability of their programs. Conclusion: It is concluded that the proposed approach can enhance the software reliability estimation testing by guiding the test case selection process by providing more descriptive and accurate results. © 2012 Elsevier B.V. All rights reserved.; Context: Most software reliability models are based on a binary notion of correctness, i.e. "successful" or "failed." However, in several instances, it is important to account of failure severity to obtain more descriptive and accurate estimates of the reliability of the software. Objective: In this paper, we develop a set of extended metrics based on the Nelson's software reliability model to account for information gained from a user's point of view regarding the severity of the observed failures. Model formulation based on multi-granularity failure severity is provided, and the proposed metrics are proved to be backward compatible. Method: In order to estimate the software reliability through testing, an extended adaptive testing strategy, namely Modified Adaptive Testing (MAT) is proposed. The use of test history information allows the resulting test process to be adaptive in the selection of tests under limited test budget. Simulations and experiments on real-life programs are conducted to evaluate the effectiveness of MAT. Results: Data show that the reliability estimates obtained using MAT (a) are closer to the "true" reliability than those obtained using random testing and (b) lead to lower variance than the techniques used for comparison, which means MAT can be applied to help testers and reliability engineers better understand the reliability of their programs. Conclusion: It is concluded that the proposed approach can enhance the software reliability estimation testing by guiding the test case selection process by providing more descriptive and accurate results. © 2012 Elsevier B.V. All rights reserved.
KeywordSoftware Engineering Software Reliability Software Testing
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/16557
Collection中国科学院软件研究所
Corresponding AuthorHu, H.(huhai.orion@gmail.com)
Recommended Citation
GB/T 7714
Hu, Hai ,Jiang, Chang-Hai ,Cai, Kai-Yuan ,et al. Enhancing software reliability estimates using modified adaptive testing[C]. Elsevier, P.O. Box 211, Amsterdam, 1000 AE, Netherlands,2013:288-300.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Hu, Hai (1)]'s Articles
[Jiang, Chang-Hai (1)]'s Articles
[Cai, Kai-Yuan (1)]'s Articles
Baidu academic
Similar articles in Baidu academic
[Hu, Hai (1)]'s Articles
[Jiang, Chang-Hai (1)]'s Articles
[Cai, Kai-Yuan (1)]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Hu, Hai (1)]'s Articles
[Jiang, Chang-Hai (1)]'s Articles
[Cai, Kai-Yuan (1)]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.