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Random testing is not only a useful testing technique in itself, but also plays a core role in many other testing methods. Hence, any significant improvement to random testing has an impact throughout the software testing community. Recently, Adaptive Random Testing (ART) was proposed as an effective alternative to random testing. This paper presents a(More)
The F-measure-the number of distinct test cases to detect the first program failure-is an effectiveness measure for debug testing strategies. We show that for random testing with replacement, the F-measure will be distributed according to the geometric distribution. A simulation study examines the distribution of two adaptive random testing methods, to(More)
Failure patterns describe typical ways in which inputs revealing program failure are distributed across the input domain—in many cases, clustered together in contiguous regions. Based on these observations several debug testing methods have been developed. We examine the upper bound of debug testing effectiveness improvements possible through making(More)
Quasi-random sequences, also known as low-discrepancy or low-dispersion sequences, are sequences of points in an n-dimensional unit hypercube. These sequences have the property that points are spread more evenly throughout the cube than random point sequences, which result in regions where there are clusters of points and others that are sparsely populated.(More)
—A web service may evolve autonomously, making peer web services in the same service composition uncertain as to whether the evolved behaviors may still be compatible to its originally collaborative agreement. Although peer services may wish to conduct regression testing to verify the original collaboration, the source code of the former service can be(More)
A web service may evolve autonomously, making peer web services in the same service composition uncertain as to whether the evolved behaviors are compatible with its original collaborative agreement. Although peer services may wish to conduct regression testing to verify the agreed collaboration, the source code of the former service may be inaccessible to(More)
Adaptive Random Testing (ART) is a method for improving the fault-finding effectiveness of random testing. Fixed-Size Candidate Set ART is the most studied variant of this approach. However, existing implementations of FSCS-ART have had substantial selection overhead, with n test cases requiring O n 2 time to generate. We describe the use of a geometric(More)