Integrating approximation methods with the generalised proportional sampling strategy
Tsong Yueh Chen, P.K. Wong, Y.T. Yu · 2003
Previous studies have shown that partition testing strategies can be very effective in detecting faults, but they can also be less effective than random testing under unfavourable circumstances. When test cases are allocated in proportion to the size of subdomains, partition testing strategies are provably better than random testing, in the sense of having a higher or equal probability of detecting at least one failure (the P-measure). Recently, the Generalised Proportional Sampling (GPS) strategy, which is always satisfiable, was proposed to relax the proportionality condition. The paper studies the use of approximation methods to generate test distributions satisfying the GPS strategy, and evaluates this proposal empirically. Our results are very encouraging, showing that on average about 98.72% to almost 100% of the test distributions obtained in this way are better than random testing in terms of the P-measure.