EvoMBT在SBST 2022工具竞赛

2022 IEEE/ACM 15th International Workshop on Search-Based Software Testing (SBST) Pub Date : 2022-05-01 DOI:10.1145/3526072.3527534

Raihana Ferdous, Chia-kang Hung, Fitsum Meshesha Kifetew, D. Prandi, A. Susi

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引用次数: 5

摘要

EvoMBT是一个基于模型的测试生成器，它使用搜索算法从给定的扩展有限状态机(EFSM)生成测试。在网络物理系统(CPS)测试的背景下，特别是在自动驾驶汽车中，我们将一组道路配置建模为EFSM，并使用EvoMBT生成用于测试汽车的不同道路。本报告简要介绍了EvoMBT，并总结了其在SBST 2022网络物理系统测试竞赛中的结果。总体而言，EvoMBT取得的结果是有希望的，其中有效性和效率得分相当好，而与多样性相关的得分需要改进。

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EvoMBT at the SBST 2022 Tool Competition

EvoMBT is a model-based test generator that uses search algorithms to generate tests from a given extended finite state machine (EFSM). In the context of Cyber-physical systems (CPS) testing, and in particular self-driving cars, we model a set of road configurations as an EFSM and use EvoMBT to generate different roads for testing the car. This report briefly introduces EvoMBT and summarizes its results in the Cyber-physical systems testing competition at SBST 2022. Overall the results achieved by EvoMBT are promising where effectiveness and efficiency scores are quite good while the scores related to diversity need improvement.

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来源期刊

2022 IEEE/ACM 15th International Workshop on Search-Based Software Testing (SBST)

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