Fuzzing the out-of-memory killer on embedded Linux: an adaptive random approach
Proceedings of the 2011 ACM Symposium on Applied Computing
Software—Practice & Experience
| Hi-index | 0.00 |
Adaptive random testing (ART) techniques have been proposed in the literature to improve the effectiveness of random testing (RT) by evenly distributing test cases over the input space. Simulations and mutation analyses of various ART techniques have demonstrated their improvements on fault detecting ability when measured by the number of test cases required to detect the first fault. In this paper, we report an experiment with ART using mutants to evaluate ART’s reliability in fault detecting ability. Our experiment discovered that ART is more reliable than RT in the sense that its degree of variation in fault detecting ability is significantly lower than RT. It is also recognized from the experiment data that the two main factors that affect ART’s reliability are the failure rate of the system under test and the regularity of the failure domain measured by the standard deviation of random test results.