6.0 Robustness Testing
Robustness testing can be seen as and extension of Boundary Value Analysis. The idea behind Robustness testing is to test for clean and dirty test cases. By clean I mean input variables that lie in the legitimate input range. By dirty I mean using input variables that fall just outside this input domain.
In addition to the aforementioned 5 testing values (min, min+, nom, max-, max) we use two more values for each variable (min-, max+), which are designed to fall just outside of the input range.
If we adapt our function f to apply to Robustness testing we find the following equation:
f = 6n + 1
I have equated this solution by the same reasoning that lead to the standard BVA equation. Each variable now has to assume 6 different values each whilst the other values are assuming their nominal value (hence the 6n), and there is again one instance whereby all variables assume their nominal value (hence the addition of the constant 1). These result can be seen in figures 6.1.
Robustness testing ensues a sway in interest, where the previous interest lied in the input to the program, the main focus of attention associated with Robustness testing comes in the expected outputs when and input variable has exceeded the given input domain. For example the NextDate problem when we an entry like the 31st June we would expect an error message to the effect of “that date does not exist; please try again”.
Robustness testing has the desirable property that it forces attention on exception handling. Although Robustness testing can be somewhat awkward in strongly typed languages it can show up altercations. In Pascal if a value is defined to reside in a certain range then and values that falls outside that range result in the run time errors that would terminate any normal execution. For this reason exception handling mandates Robustness testing.
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