Building reliable Cyber-physical systems often requires engineers to search for software defects. Search-based software testing (SBST) is a standard technology that supports this activity. To increase practical adoption, industries need empirical evidence of the usefulness of SBST techniques on different benchmarks. To address this need, this replication study reports on our experience assessing the usefulness of SBST in generating failure-revealing test cases. Our study subject is within the electric bike (e-Bike) domain and concerns the software controller of an e-Bike motor. We assessed the effectiveness and efficiency of HECATE, an SBST framework for Simulink models. HECATE successfully identified failure-revealing test cases in practical time. We present the lessons learned, the relevance of our results for industrial applications, and the improvement in the state of practice.

(2026). Test Case Generation for Simulink Models: An Experience from the E-Bike Domain . Retrieved from https://hdl.handle.net/10446/326145

Test Case Generation for Simulink Models: An Experience from the E-Bike Domain

Bombarda, Andrea;Minervini, Marcello;Gargantini, Angelo;Menghi, Claudio
2026-01-01

Abstract

Building reliable Cyber-physical systems often requires engineers to search for software defects. Search-based software testing (SBST) is a standard technology that supports this activity. To increase practical adoption, industries need empirical evidence of the usefulness of SBST techniques on different benchmarks. To address this need, this replication study reports on our experience assessing the usefulness of SBST in generating failure-revealing test cases. Our study subject is within the electric bike (e-Bike) domain and concerns the software controller of an e-Bike motor. We assessed the effectiveness and efficiency of HECATE, an SBST framework for Simulink models. HECATE successfully identified failure-revealing test cases in practical time. We present the lessons learned, the relevance of our results for industrial applications, and the improvement in the state of practice.
2026
Marzella, Michael; Bombarda, Andrea; Minervini, Marcello; Bisceglia, Nunzio Marco; Gargantini, Angelo Michele; Menghi, Claudio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/326145
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