Optimizing combinatorial input-output based relations testing using Ant Colony algorithm
Combinatorial software testing involves more than one parameter interaction with each other. Input-output based relations (IOR) is one of the combinatorial testing's strategies. This form of testing is advantageous compared to others. IOR only focuses on program output and interactions between...
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| Vydáno v: | 2016 3rd International Conference on Electronic Design (ICED) s. 586 - 590 |
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| Hlavní autoři: | , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.08.2016
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| Témata: | |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Combinatorial software testing involves more than one parameter interaction with each other. Input-output based relations (IOR) is one of the combinatorial testing's strategies. This form of testing is advantageous compared to others. IOR only focuses on program output and interactions between certain input values parameters. However, limited research is available for IOR strategy. Even though IOR strategy has been proven to minimize test suite size due to its characteristics, the size can be reduced by properly select the "don't care value" of the test cases. In order to improve the result, an optimization algorithm approach is proposed to be adopted with the strategy. This paper focuses on the Ant Colony System (ACS) which is boosted by a few enhancements on combinatorial interactions, heuristic value, fitness functions and number of ants to develop an IOR strategy. ACS has been chosen because it is known to generate a smaller size of test suit for another combinatorial testing strategy, which is a variable strength strategy. Owing to this, it is hoped that ACS can deliver promising results regarding implementation of IOR strategy. |
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| DOI: | 10.1109/ICED.2016.7804713 |