Automatic test data generation is a hot topic in recent software testing research. Various techniques have been proposed with different emphases. Among them, most of the methods are based on Genetic Algorithms (GA). However, whether it is the best Metaheuristic method for such a problem remains unclear. In this paper, we choose to use another approach which arms a GA with an intensive local searcher (the so-called Memetic Algorithm (MA) according to the recent terminology). The idea of incorporating local searcher is based on the observations from many real-world programs. It turns out the results outperform many other known Metaheuristic methods so far. We argue the needs of local search for software testing in the discussion of the paper.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0713106-201239 |
| Date | 13 July 2006 |
| Creators | Wang, Hsiu-Chi |
| Contributors | Chia-Mei Chen, Sheng-Tzong Cheng, Yuh-Jiuan Tsay, Bingchiang Jeng |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0713106-201239 |
| Rights | unrestricted, Copyright information available at source archive |
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