Loading...
Please wait, while we are loading the content...
Similar Documents
Adaptive random testing by balancing
| Content Provider | ACM Digital Library |
|---|---|
| Author | Chen, T. Y. Huang, De Hao Kuo, F.-C |
| Abstract | Adaptive Random Testing (ART) is an effective improvement of Random Testing (RT). It is based on the observation that failure-causing inputs tend to be clustered together. ART, therefore, proposes to have randomly selected test cases being more evenly spread throughout the input domain by employing the location information of the successful test cases (those that have been executed but do not reveal failures). Based on this intuition, several ART methods have been developed. However, the fault-detection capability of some ART methods is compromised in high dimensional input domains. To improve the fault-detection capability in high dimensional input domains, this paper proposes an innovative ART method using the notion of balancing. Simulation results show that the new method has improved the fault-detection capability in high dimensional input domains. |
| Starting Page | 2 |
| Ending Page | 9 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781595938817 |
| DOI | 10.1145/1292414.1292418 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2007-11-06 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Random testing Software testing Balancing Adaptive random testing |
| Content Type | Text |
| Resource Type | Article |
