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DC Field | Value | Language |
---|---|---|
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 |
Appears in Collections: | Department of Computer Science and Information Systems |
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