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A key objective of software testing is to find program errors that cause failure in software, at less cost. One basic testing technique is random testing (RT), but many researchers have criticised its failure-detection effectiveness. Several researchers have proposed that an enhancement of the failure-detection effectiveness of RT is achieved if test cases are evenly spread within the input domain. Adaptive RT (ART) describes a family of algorithms that employ various strategies to evenly and randomly spread test cases. Fixed sized candidate set ART (FSCS-ART) is an ART algorithm that has gained many research studies far and wide; however, the high distance computations make its algorithm computationally expensive. The authors propose a new ART method that restricts distance computations to only test cases inside an exclusion zone. The experimental results show that the new ART method not only improves RT but also provides failure-detection effectiveness similar to FSCS-ART, while significantly minimising computation overhead.

Adaptive random testing (ART) has been proposed to enhance the effectiveness of random testing (RT) through more even spreading of the test cases. In particular, restricted random testing (RRT) is an ART algorithm based on the intuition of skipping all the candidate test cases that are within the neighborhoods (or zones) of previously executed test cases. RRT has higher effectiveness than RT in terms of failure detection but incurs a higher time cost. In this paper, we aim to further reduce the time costs for RRT and improve the effectiveness for RT and ART methods. We propose a proactive technique known as ''RRT by largest available zone'' (RRT-LAZ). Like RRT, RRT-LAZ first defines an exclusion zone around every executed test case in order to determine the available zones. Unlike the original RRT, RRT-LAZ then compares all the available zones to proactively pick the largest one, from which the next test case is randomly generated. Both simulation analyses and empirical studies have been employed to investigate the efficiency and effectiveness of RRT-LAZ in relation to RT and related ART algorithms. The results show that RRT-LAZ has significantly lower time costs than RRT. Furthermore, RRT-LAZ is more effective than RT and related ART methods for block failure patterns in low-dimensional input spaces. In general, since RRT-LAZ employs a proactive technique instead of a passive one in generating next cases, it is much more cost-effective than RRT. RRT-LAZ is also more cost-effective than RT and other ART methods that we have studied. INDEX TERMS Software testing, random testing, adaptive random testing, restricted random testing, exclusion zone, largest available zone. I. BACKGROUND

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