| dc.contributor.author |
Pachauri, A. |
|
| dc.date.accessioned |
2023-01-18T10:27:07Z |
|
| dc.date.available |
2023-01-18T10:27:07Z |
|
| dc.date.issued |
2015 |
|
| dc.identifier.uri |
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7154969&isnumber=7154914 |
|
| dc.identifier.uri |
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8549 |
|
| dc.description.abstract |
In this paper we present a novel approach for
fitness computation for test data generation using genetic
algorithm. Fitness computation is a two-step process. In the first
step a target node sequence is determined and in the second step
the actual execution path is compared with the target node
sequence to compute fitness. Fitness computation uses both
branch and path information. Experiments indicate that the
described fitness technique results in significant improvement in
search performance |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
IEEE |
en_US |
| dc.subject |
Computer Science |
en_US |
| dc.subject |
Program test data generation |
en_US |
| dc.subject |
Search-based software testing |
en_US |
| dc.subject |
Genetic algorithm |
en_US |
| dc.title |
A Path and Branch Based Approach to Fitness Computation for Program Test Data Generation using Genetic Algorithm |
en_US |
| dc.type |
Article |
en_US |