Data Diversity: An Approach to Software Fault Tolerance
IEEE Transactions on Computers - Fault-Tolerant Computing
An empirical study of the reliability of UNIX utilities
Communications of the ACM
Proportional sampling strategy: a compendium and some insights
Journal of Systems and Software
Software Fault Interactions and Implications for Software Testing
IEEE Transactions on Software Engineering
Enhancing adaptive random testing in high dimensional input domains
Proceedings of the 2007 ACM symposium on Applied computing
A genetic approach for random testing of database systems
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Adaptive Random Testing by Exclusion through Test Profile
QSIC '10 Proceedings of the 2010 10th International Conference on Quality Software
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Adaptive random testing (ART) has been developed as an enhancement of random testing (RT) in terms of failure-detection capability, and has been widely investigated. When a given faulty program has an N-dimensional input domain (N 1), a straightforward approach (abbreviated as ART-C) is to implement parallelism into ART algorithms, which generates one N-dimensional test case by computing each of its N coordinates independently and in parallel. Intuitively, ART-C using a specific ART algorithm may not be a great test case selection, because an even spread on each coordinate does not necessarily imply the even spread over the whole input domain. However, actual failure-detection capabilities of implementations of ART-C, so far, have not yet been investigated. In this paper, we conduct on one particular ART algorithm named fixed-size-candidate-set ART (FSCS-ART), and design some simulations to analyze the failure-detection effectiveness of the corresponding implementation of ART-C (that is, FSCS-ART-C). The experimental results show that FSCS-ART-C performs more effectively than FSCS-ART in some scenarios such as high dimensional input domains, which provides useful information for testers to decide whether and when to use FSCS-ART-C. In addition, our study also presents some implications about how to improve the effectiveness of ART.