Black-box test reduction using input-output analysis

Abstract

Test reduction is an important issue in black-box testing. The number of possible black-box tests for any non-trivial software application is extremely large. For the class of programs with multiple inputs and outputs, the number of possible tests grows very rapidly as combinations of input test data are considered. In this paper, we introduce an approach to test reduction that uses automated input-output analysis to identify relationships between program inputs and outputs. Our initial experience with the approach has shown that it can significantly reduce the number of black-box tests.