Adaptive random testing through dynamic partitioning

Adaptive random testing (ART) describes a family of algorithms for generating random test cases that have been experimentally demonstrated to have greater fault-detection capacity than simple random testing. We outline and demonstrate two new ART algorithms, and demonstrate experimentally that they offer similar performance advantages, with considerably lower overhead than other ART algorithms.

[1]  Tsong Yueh Chen,et al.  On the Relationship Between Partition and Random Testing , 1994, IEEE Trans. Software Eng..

[2]  Elaine J. Weyuker,et al.  Analyzing Partition Testing Strategies , 1991, IEEE Trans. Software Eng..

[3]  Harlan D. Mills,et al.  Engineering software under statistical quality control , 1990, IEEE Software.

[4]  Tsong Yueh Chen,et al.  Proportional sampling strategy: guidelines for software testing practitioners , 1996, Inf. Softw. Technol..

[5]  Tsong Yueh Chen,et al.  Proportional sampling strategy: a compendium and some insights , 2001, J. Syst. Softw..

[6]  Ps Loo,et al.  Random testing revisited , 1988 .

[7]  Dave Towey,et al.  Restricted Random Testing , 2002, ECSQ.

[8]  Lee J. White,et al.  A Domain Strategy for Computer Program Testing , 1980, IEEE Transactions on Software Engineering.

[9]  Glenford J. Myers,et al.  Art of Software Testing , 1979 .