A revisit of adaptive random testing by restriction

Kwok Ping Chan, Tsong Yueh Chen, Fei Ching Kuo, Dave Towey

Research output: Journal PublicationConference articlepeer-review

30 Citations (Scopus)


Adaptive Random Testing is a Black Box testing method based on the intuition that Random Testing failure-finding efficiency can be improved upon, in certain situations, by ensuring a more widespread and evenly distributed spread of test cases in the input domain. One way of achieving this distribution is through the use of exclusion zones and restriction, resulting in a method called Restricted Random Testing (RRT). Recent investigations into the RRT method have revealed several interesting and significant insights. A method of reducing the computational overheads of testing methods by partitioning an input domain, and applying the method to only one of the subdomains, mapping the test cases to other subdomains, has recently been introduced. This method, called Mirroring, in addition to alleviating computational costs, has some properties which fit nicely with the insights into RRT, offering solutions to some possible shortcomings of RRT. . In this paper we discuss the RRT method and additional insights; we explain Mirroring; and we detail applications of Mirroring to RRT. The Mirror RRT method proves to be a very attractive variation of RRT.

Original languageEnglish
Pages (from-to)78-85
Number of pages8
JournalProceedings - International Computer Software and Applications Conference
Publication statusPublished - 2004
Externally publishedYes
EventProceedings of the 28th Annual International Computer Software and Applications Conference, COMPSAC 2004 - Hong Kong, China, Hong Kong
Duration: 28 Sept 200430 Sept 2004


  • Adaptive Random Testing
  • Mirroring
  • Random Testing
  • Restricted Random Testing
  • Software Testing

ASJC Scopus subject areas

  • Software
  • Computer Science Applications


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