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
Art of Software Testing
Engineering Software Under Statistical Quality Control
IEEE Software
Massive Stochastic Testing of SQL
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Random Program Generator for Java JIT Compiler Test System
QSIC '03 Proceedings of the Third International Conference on Quality Software
Adaptive Random Testing Through Dynamic Partitioning
QSIC '04 Proceedings of the Quality Software, Fourth International Conference
Adaptive Random Testing by Localization
APSEC '04 Proceedings of the 11th Asia-Pacific Software Engineering Conference
CUTE: a concolic unit testing engine for C
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
An empirical study of the robustness of Windows NT applications using random testing
WSS'00 Proceedings of the 4th conference on USENIX Windows Systems Symposium - Volume 4
ASIAN'04 Proceedings of the 9th Asian Computing Science conference on Advances in Computer Science: dedicated to Jean-Louis Lassez on the Occasion of His 5th Cycle Birthday
Directed random reduction of combinatorial test suites
Proceedings of the 2nd international workshop on Random testing: co-located with the 22nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2007)
A genetic approach for random testing of database systems
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
An empirical evaluation of a language-based security testing technique
CASCON '09 Proceedings of the 2009 Conference of the Center for Advanced Studies on Collaborative Research
Software—Practice & Experience
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Adaptive Random Testing (ART) is an enhancement of Random Testing (RT). It is known when ART can outperform RT and when it cannot. Previous studies assumed that the test cases are selected with replacement. It is unknown whether selection without replacement can enhance the effectiveness of ART and also RT. Our studies include whether ART outperforms RT because it evenly spreads test cases or it generates fewer duplicate test cases, whether the input domain type and size have an impact on the effectiveness of ART, whether ART can still outperform RT when there exists only one single failure-causing input (in that case, failure-causing inputs do not cluster together). This study comprehends our understandings about whether ART is really better than RT.