Feedback-Directed Unit Test Generation for C/C++ using Concolic Execution

Pranav Garg and Franjo Ivancic and Gogul Balakrishnan and Naoto Maeda and Aarti Gupta

Abstract: In industry, software testing and coverage-based metrics are the predominant techniques to check correctness of software. This paper addresses automatic unit test generation for programs written in C/C++. The main idea is to improve the coverage obtained by feedback-directed random test generation methods, by utilizing concolic execution on the generated test drivers. Furthermore, for programs with numeric computations, we employ non-linear solvers in a lazy manner to generate new test inputs. These techniques significantly improve the coverage provided by a feedback-directed random unit testing framework, while retaining the benefits of full automation. We have implemented these techniques in a prototype platform, and describe promising experimental results on a number of C/C++ open source benchmarks.

Paper available soon.