Pairwise Test Data Generation based on Flower Pollination Algorithm
Owing to an exponential increase in computational time associated with increasing number of system components, exhaustive testing is increasingly becomes impractical. Here, many researchers opt to adopt pairwise testing to minimize the overall number of tests. Recently, many existing works are focus...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universiti Malaya
2017
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/19474/ http://umpir.ump.edu.my/id/eprint/19474/ http://umpir.ump.edu.my/id/eprint/19474/ http://umpir.ump.edu.my/id/eprint/19474/1/mjcs.pdf |
| Summary: | Owing to an exponential increase in computational time associated with increasing number of system components, exhaustive testing is increasingly becomes impractical. Here, many researchers opt to adopt pairwise testing to minimize the overall number of tests. Recently, many existing works are focusing on the use of Search-Based algorithms as the basis of the implementation algorithm; however, there is no single strategy that can be the best for all cases. Currently, researches on Flower Pollination Algorithm (FPA) are very active and its applications have been proven successes to solve many problems. This paper proposes a new search-based strategy for generating the pairwise test suite, called Pairwise Flower Strategy (PairFS). The main feature of PairFS is that it is the first pairwise strategy that adopts FPA as its core implementation. To evaluate and benchmark our proposed strategy against existing strategies, several existing comparative experiments are adopted. The results of the experiment show that in many cases PairFS are more efficient than the existing strategies in terms of the test suite size. |
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