A decision-theoretic approach to the test allocation problem in partition testing

Tsong Yueh Chen, Yuen Tak Yu

Research output: Journal Publications and ReviewsRGC 22 - Publication in policy or professional journal

7 Citations (Scopus)

Abstract

A partition testing strategy consists of two components: a partitioning scheme which determines the way in which the program's input domain is partitioned into subdomains, and an allocation of test cases which determines the exact number of test cases selected from each subdomain. This paper investigates the problem of determining the test allocation when a particular partitioning scheme has been chosen. We show that this problem can be formulated as a classic problem of decision-making under uncertainty, and analyze several well known criteria to resolve this kind of problem. We present algorithms that solve the test allocation problem based on these criteria, and evaluate these criteria by means of a simulation experiment. We also discuss the applicability and implications of applying these criteria in the context of partition testing.
Original languageEnglish
Pages (from-to)733-745
JournalIEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans
Volume32
Issue number6
DOIs
Publication statusPublished - Nov 2002

Research Keywords

  • Decision under uncertainty
  • Optimal test distribution
  • Partition testing
  • Random testing
  • Software engineering
  • Software testing

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