Adaptive Random Testing: The ART of test case diversity

  • Authors:

  • Tsong Yueh Chen;Fei-Ching Kuo;Robert G. Merkel;T. H. Tse

  • Affiliations:

  • Faculty of Information and Communication Technologies, Swinburne University of Technology, John St, Hawthorn 3122, Australia;Faculty of Information and Communication Technologies, Swinburne University of Technology, John St, Hawthorn 3122, Australia;Faculty of Information and Communication Technologies, Swinburne University of Technology, John St, Hawthorn 3122, Australia;Department of Computer Science, The University of Hong Kong, Pokfulam, Hong Kong

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2010

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Abstract

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 synthesis of the most important research results related to ART. In the course of our research and through further reflection, we have realised how the techniques and concepts of ART can be applied in a much broader context, which we present here. We believe such ideas can be applied in a variety of areas of software testing, and even beyond software testing. Amongst these ideas, we particularly note the fundamental role of diversity in test case selection strategies. We hope this paper serves to provoke further discussions and investigations of these ideas.