Abstract
Recently, adaptive random testing (ART) has been developed to enhance the fault-detection effectiveness of random testing (RT). It has been known in general that the fault-detection effectiveness of ART depends on the distribution of failure-causing inputs, yet this understanding is in coarse terms without precise details. In this paper, we conduct an in-depth investigation into the factors related to the distribution of failure-causing inputs that have an impact on the fault-detection effectiveness of ART. This paper gives a comprehensive analysis of the favourable conditions for ART. Our study contributes to the knowledge of ART and provides useful information for testers to decide when it is more cost-effective to use ART.
| Original language | English |
|---|---|
| Pages (from-to) | 805-825 |
| Number of pages | 21 |
| Journal | International Journal of Software Engineering and Knowledge Engineering |
| Volume | 17 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Dec 2007 |
| Externally published | Yes |
Free Keywords
- Adaptive random testing
- ART F-ratio
- Distribution of failure-causing inputs
- Fault-detection effectiveness
- Random testing
- Software testing
ASJC Scopus subject areas
- Software
- Computer Networks and Communications
- Computer Graphics and Computer-Aided Design
- Artificial Intelligence
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