QA and Testing

White Paper: L&T Infotech

Every organization should have well-organized and effective testing strategies in order to increase test efficiency and deliver high quality software. Test data is one of the most important factors in overall testing life cycle. Scenario-specific, realistic, right-sized, masked test data created in test environments ensures the following: - Scenario-specific test data availability before test execution increases test efficiency/quality and reduces overall testing cycle time. - Realistic test data in lower test regions reduces production defect leakages. - Right-sized test data in test environments reduces space utilization and increases the response time. - Masked test data ensures security compliance

White Paper: UST Global

The Orthogonal Array Testing Strategy (OATS) is a systematic, statistical way of testing pair-wise interactions. This can be used to reduce the number of combinations and provide maximum coverage with a minimum number of test cases. OAT is an array of values in which each column represents a variable - factor that can take a certain set of values called levels. Each row represents a test case. In OAT, the factors are combined pair wise rather than representing all possible combinations of factors and levels. OATS has limitations when the factors are dependent and existing OATS supporting tools doesn’t provide an option to increase test coverage. Firstly Orthogonal Array Testing Strategy introduces in this paper, and then proceeds with an analysis on scope of OATS in current QA world. Also propose an automated testing tool ‘Extended OATS’ to overcome the limitations of OATS and to resolve the most common challenge faced in testing community – ‘Ensure optimum test coverage and increase defect removal efficiency.’