Test case generation for visual contracts using AI planning

Abstract

In this paper, we propose a novel approach for computing test case preambles using visual contracts and AI Planning. In unit testing, preambles are required for setting the class under test into a controlled state (prestate). The class operation can then be invoked with test inputs. In previous research, we have used model checking for computing preambles. In this paper, we show how preamble computation is conducted by AI Planning and discuss its differences to model checking.