Fast, Automatic, and Nearly Complete Structural Unit-Test Generation Combining Genetic Algorithms and Formal Methods

Abstract

Software testing is a time consuming and error prone activity, mostly manual in most industries. One approach to increase productivity is to automatically generate tests. In this paper, we focus on automatic generation of structural unit tests of safety-critical embedded software. Our purpose is to make a tool that integrates seamlessly with existing test processes in industry. We use genetic algorithms and automatic stub generation to quickly and automatically produce test cases satisfying test objectives of a given coverage criteria, using only the software under test as input. Moreover, we combine those genetic algorithms with formal methods to determine unfeasible test objectives and help on the coverage of difficult test objectives. We implemented our approach in a tool and tested it on a real-world industrial project, demonstrating that our approach can reliably generate test cases when feasible or demonstrate they are unfeasible for 99% of the MC/DC test objectives in about half an hour for 82,000 lines of C code with integer data.