Generation of test data using meta heuristic approach
Software testing is of huge importance to development of any software. The prime focus is to minimize the expenses on the testing. In software testing the major problem is generation of test data. Several metaheuristic approaches in this field have become very popular. The aim is to generate the opt...
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| creator | Srivastava, P.R. Ramachandran, V. Kumar, M. Talukder, G. Tiwari, V. Sharma, P. |
| description | Software testing is of huge importance to development of any software. The prime focus is to minimize the expenses on the testing. In software testing the major problem is generation of test data. Several metaheuristic approaches in this field have become very popular. The aim is to generate the optimum set of test data, which would still not compromise on exhaustive testing of software. Our objective is to generate such efficient test data using genetic algorithm and ant colony optimization for a given software. We have also compared the two approaches of software testing to determine which of these are effective towards generation of test data and constraints if any. |
| doi_str_mv | 10.1109/TENCON.2008.4766707 |
| format | Conference Proceeding |
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The prime focus is to minimize the expenses on the testing. In software testing the major problem is generation of test data. Several metaheuristic approaches in this field have become very popular. The aim is to generate the optimum set of test data, which would still not compromise on exhaustive testing of software. Our objective is to generate such efficient test data using genetic algorithm and ant colony optimization for a given software. We have also compared the two approaches of software testing to determine which of these are effective towards generation of test data and constraints if any.</abstract><pub>IEEE</pub><doi>10.1109/TENCON.2008.4766707</doi><tpages>6</tpages></addata></record> |
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| identifier | ISSN: 2159-3442 |
| ispartof | TENCON 2008 - 2008 IEEE Region 10 Conference, 2008, p.1-6 |
| issn | 2159-3442 2159-3450 |
| language | eng |
| recordid | cdi_ieee_primary_4766707 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Ant colony optimization Ant Colony Optimization (ACO) Chemicals Computer science Fitness Function Genetic Algorithm (GA) Genetic algorithms Genetic mutations Information systems Search problems Software testing System testing Wheels |
| title | Generation of test data using meta heuristic approach |
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