There are a number of black box testing techniques; the one that is being discussed in this post is the orthogonal array testing. This technique provides a systematic as well as statistical strategy for testing software. The number of inputs to the system in this technique is small but large enough for testing each and every possible input as in exhaustive testing. This technique has proved to be quite helpful in discovering errors that show a faulty logic in the software systems. Orthogonal arrays can be applied in various testing types such as following:

- User interface or UI testing

- System testing

- Regression testing

- Configuration testing

- Performance testing and so on.

The permutations for the factor levels that consist of only one treatment have to be chosen in an uncorrelated way, so that every single treatment gives you a piece of information that is different from the others. The advantage of organizing testing in such a way is that a minimum number of experiments are required for gathering same information. Orthogonality is a property exhibited by the orthogonal vectors. Properties exhibited by the orthogonal vectors are mentioned below:

- Information conveyed by each vector is different from the information by other vectors in the sequence. That is, as we mentioned information conveyed by each treatment is unique to it. This is important otherwise there will be redundancy.

- It is easy to separate these signals on a linear addition.

- All the vectors are statistically independent of each other which means that there is no correlation between them.

- When these individual components are added linearly, the result is an arithmetic sum.

Suppose a system is having 3 parameters each of which has 3 values. We require total 27 test cases for testing all of the parameter combinations which is quite time consuming. So we use an orthogonal array for selecting a combination subset from these combinations. As a result of using the orthogonal array testing, maximization of the test coverage area is possible. At the same time this minimizes the number of test cases that have to be considered for testing. The pair that is selected is assumed to have the maximum number of defects. The technique works based up on this assumption. These many combinations are sufficient for catching the fault. The interaction of the input parameters between themselves has also to be considered. The array is said to be orthogonal because the occurrence of all pair wise combinations is once. The results of the test cases are assessed as follows:

- Single mode faults

- Double mode faults

- Multimode faults

Below mentioned are the major benefits of using this technique:

- The testing cycle time is reduced.

- The analysis process gets simpler

- Test cases are balanced which means that the defect isolation and performance assessments are straightforward.

- Saves up on costs when compared to the pair-wise testing. The coverage to all the defects can only be provided by testing all the combinations that are possible. But our schedule and budget often do not permit this. Therefore we are forced to select only a sample of the combinations from the test domain. Orthogonal array testing is a means for generating samples that provide high coverage for the validation of test domain effectively. This has made the technique particularly useful in the integration testing and testing of the configurable options. Software testers often face a dilemma during selection of the test cases. The quality of the software cannot be tested but only the defects can be detected. And the exhaustive testing is difficult even in the small systems.

- User interface or UI testing

- System testing

- Regression testing

- Configuration testing

- Performance testing and so on.

The permutations for the factor levels that consist of only one treatment have to be chosen in an uncorrelated way, so that every single treatment gives you a piece of information that is different from the others. The advantage of organizing testing in such a way is that a minimum number of experiments are required for gathering same information. Orthogonality is a property exhibited by the orthogonal vectors. Properties exhibited by the orthogonal vectors are mentioned below:

- Information conveyed by each vector is different from the information by other vectors in the sequence. That is, as we mentioned information conveyed by each treatment is unique to it. This is important otherwise there will be redundancy.

- It is easy to separate these signals on a linear addition.

- All the vectors are statistically independent of each other which means that there is no correlation between them.

- When these individual components are added linearly, the result is an arithmetic sum.

Suppose a system is having 3 parameters each of which has 3 values. We require total 27 test cases for testing all of the parameter combinations which is quite time consuming. So we use an orthogonal array for selecting a combination subset from these combinations. As a result of using the orthogonal array testing, maximization of the test coverage area is possible. At the same time this minimizes the number of test cases that have to be considered for testing. The pair that is selected is assumed to have the maximum number of defects. The technique works based up on this assumption. These many combinations are sufficient for catching the fault. The interaction of the input parameters between themselves has also to be considered. The array is said to be orthogonal because the occurrence of all pair wise combinations is once. The results of the test cases are assessed as follows:

- Single mode faults

- Double mode faults

- Multimode faults

Below mentioned are the major benefits of using this technique:

- The testing cycle time is reduced.

- The analysis process gets simpler

- Test cases are balanced which means that the defect isolation and performance assessments are straightforward.

- Saves up on costs when compared to the pair-wise testing. The coverage to all the defects can only be provided by testing all the combinations that are possible. But our schedule and budget often do not permit this. Therefore we are forced to select only a sample of the combinations from the test domain. Orthogonal array testing is a means for generating samples that provide high coverage for the validation of test domain effectively. This has made the technique particularly useful in the integration testing and testing of the configurable options. Software testers often face a dilemma during selection of the test cases. The quality of the software cannot be tested but only the defects can be detected. And the exhaustive testing is difficult even in the small systems.

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