EvoMBT at the SBFT 2023 Tool Competition

被引：2

作者：

Ferdous, Raihana ^{[1
]}

Hung, Chia-kang ^{[1
]}

Kifetew, Fitsum ^{[1
]}

Prandi, Davide ^{[1
]}

Susi, Angelo ^{[1
]}

机构：

[1] Fdn Bruno Kessler, Trento, Italy

来源：

2023 IEEE/ACM INTERNATIONAL WORKSHOP ON SEARCH-BASED AND FUZZ TESTING, SBFT | 2023年

关键词：

search-based testing; model-based testing; cyber-physical systems; advanced driver assistance systems;

D O I：

10.1109/SBFT59156.2023.00018

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

EvoMBT is a model-based test generator that principally 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 use a model of road configurations from which EvoMBT generates different roads for testing the car. This report introduces EvoMBT and reports the results it achieved in the Cyber-physical systems testing competition at SBFT 2023. EvoMBT was able to trigger several out-of-bound events and stood fourth in the overall ranking consisting of a total of six

引用

页码：59 / 60

页数：2

共 5 条

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