Use of Orthogonal Arrays and Design of Experiments via Taguchi methods in Software Testing

To solve the problem of great number of test cases, and to force the configuration testing to be effective, combinatorial testing is proposed, using an Orthogonal Array Testing Strategy (OATS) as a systematic, statistical way of testing pair-wise interactions. This combinatorial approach to software testing uses models to generate a minimal number of test inputs so that selected combinations of input values are covered. The OAT method can simultaneously reduce testing costs, product introduction delays, and faults going to the field by generating test cases that are more efficient and thorough in finding faults. Often the result is a 50% reduction in the number of tests and detection of more faults. An advantage of the Taguchi method application in Software Testing is that it emphasizes a mean performance characteristic (Defect fixing time and cost of software Quality) value close to the target value rather than a value within certain specification limits, thus improving the product quality. Additionally, Taguchi's method for experimental design is straightforward and easy to apply as we did for defect Cost to fix [$] and Total Resolution time [Days] minimisation versus controlled factors: Severity, Complexity and engineers Experience to many engineering situations, making it a powerful yet simple tool. Key-Words: Software testing, Bug fixing, Resources allocation, Orthogonal Array, DOE, Taguchi method