A Scalable Monte-Carlo Test-Case Generation Tool for Large and Complex Simulink Models

Abstract

MATLAB/Simulink is the de facto standard tool for the model-based development (MBD) of control software for automotive systems. A model developed in MBD is called a Simulink model and, for real automotive systems, involves complex computation as well as tens of thousands of blocks. In this paper, we propose an automated test generation tool for such large and complex Simulink models. The tool provides functions for (1) automatically generating high-coverage test-suites for practical models, which cannot be handled by Simulink Design Verifier (SLDV), and (2) measuring decision, condition and MC/DC coverage much more efficiently than Simulink Coverage (SLC). This automatic test-suite generation adopts a Monte-Carlo method with templates of test cases. Our experimental evaluation shows that the tool can provide test suites against practical implementation models with higher coverage and shorter execution times than SLDV.