Dynamic Solution of Linear Constraints for Test Case Generation

Abstract

The manual generation of test cases for unit tests is tedious. We have developed the tool Muggl, which generates test cases based on symbolic execution and constraint solving. Solving constraints for this purpose is no trivial task and greatly attributes to the total runtime. Hence, we developed a solver for linear constraints adapted to the special needs of Muggl. It takes into account the particularities of constraint retrieval through symbolic execution. Specifically, it is capable of incremental addition and backtracking of constraints. Moreover, we have developed an approach to avoid rounding errors.