The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
pandangan teks lengkap
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MATLAB/Simulink ialah alat standard de facto untuk pembangunan berasaskan model (MBD) perisian kawalan untuk sistem automotif. Model Simulink yang dibangunkan dalam MBD untuk sistem automotif sebenar melibatkan pengiraan yang kompleks serta berpuluh-puluh ribu blok. Dalam makalah ini, kami menumpukan pada kriteria liputan keputusan (DC), liputan keadaan (CC) dan liputan keadaan/keputusan (MC/DC) yang diubah suai, dan mencadangkan kaedah penjanaan suite ujian Monte-Carlo untuk model Simulink yang besar dan kompleks. Dalam kaedah tersebut, kes ujian calon dijana dengan memberikan nilai rawak kepada parameter templat isyarat dengan bentuk gelombang tertentu. Kami cuba mencari calon yang boleh menyumbang dalam ruang carian yang munasabah dan boleh difahami, yang ditentukan oleh satu set templat. Kami melaksanakan kaedah sebagai alat dan penilaian percubaan kami menunjukkan bahawa alat itu mampu menjana suite ujian untuk model pelaksanaan industri dengan liputan yang lebih tinggi dan masa pelaksanaan yang lebih pendek daripada Pengesah Reka Bentuk Simulink. Selain itu, alat ini termasuk enjin pengukuran liputan pantas, yang menunjukkan prestasi yang lebih baik daripada Liputan Simulink dalam percubaan kami.
Takashi TOMITA
Japan Advanced Institute of Science and Technology
Daisuke ISHII
University of Fukui
Toru MURAKAMI
Gaio Technology Co.
Shigeki TAKEUCHI
Gaio Technology Co.
Toshiaki AOKI
Japan Advanced Institute of Science and Technology
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Salinan
Takashi TOMITA, Daisuke ISHII, Toru MURAKAMI, Shigeki TAKEUCHI, Toshiaki AOKI, "Template-Based Monte-Carlo Test-Suite Generation for Large and Complex Simulink Models" in IEICE TRANSACTIONS on Fundamentals,
vol. E103-A, no. 2, pp. 451-461, February 2020, doi: 10.1587/transfun.2019MAP0010.
Abstract: MATLAB/Simulink is the de facto standard tool for the model-based development (MBD) of control software for automotive systems. A Simulink model developed in MBD for real automotive systems involves complex computation as well as tens of thousands of blocks. In this paper, we focus on decision coverage (DC), condition coverage (CC) and modified condition/decision coverage (MC/DC) criteria, and propose a Monte-Carlo test suite generation method for large and complex Simulink models. In the method, a candidate test case is generated by assigning random values to the parameters of signal templates with specific waveforms. We try to find contributable candidates in a plausible and understandable search space, specified by a set of templates. We implemented the method as a tool, and our experimental evaluation showed that the tool was able to generate test suites for industrial implementation models with higher coverages and shorter execution times than Simulink Design Verifier. Additionally, the tool includes a fast coverage measurement engine, which demonstrated better performance than Simulink Coverage in our experiments.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2019MAP0010/_p
Salinan
@ARTICLE{e103-a_2_451,
author={Takashi TOMITA, Daisuke ISHII, Toru MURAKAMI, Shigeki TAKEUCHI, Toshiaki AOKI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Template-Based Monte-Carlo Test-Suite Generation for Large and Complex Simulink Models},
year={2020},
volume={E103-A},
number={2},
pages={451-461},
abstract={MATLAB/Simulink is the de facto standard tool for the model-based development (MBD) of control software for automotive systems. A Simulink model developed in MBD for real automotive systems involves complex computation as well as tens of thousands of blocks. In this paper, we focus on decision coverage (DC), condition coverage (CC) and modified condition/decision coverage (MC/DC) criteria, and propose a Monte-Carlo test suite generation method for large and complex Simulink models. In the method, a candidate test case is generated by assigning random values to the parameters of signal templates with specific waveforms. We try to find contributable candidates in a plausible and understandable search space, specified by a set of templates. We implemented the method as a tool, and our experimental evaluation showed that the tool was able to generate test suites for industrial implementation models with higher coverages and shorter execution times than Simulink Design Verifier. Additionally, the tool includes a fast coverage measurement engine, which demonstrated better performance than Simulink Coverage in our experiments.},
keywords={},
doi={10.1587/transfun.2019MAP0010},
ISSN={1745-1337},
month={February},}
Salinan
TY - JOUR
TI - Template-Based Monte-Carlo Test-Suite Generation for Large and Complex Simulink Models
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 451
EP - 461
AU - Takashi TOMITA
AU - Daisuke ISHII
AU - Toru MURAKAMI
AU - Shigeki TAKEUCHI
AU - Toshiaki AOKI
PY - 2020
DO - 10.1587/transfun.2019MAP0010
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E103-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2020
AB - MATLAB/Simulink is the de facto standard tool for the model-based development (MBD) of control software for automotive systems. A Simulink model developed in MBD for real automotive systems involves complex computation as well as tens of thousands of blocks. In this paper, we focus on decision coverage (DC), condition coverage (CC) and modified condition/decision coverage (MC/DC) criteria, and propose a Monte-Carlo test suite generation method for large and complex Simulink models. In the method, a candidate test case is generated by assigning random values to the parameters of signal templates with specific waveforms. We try to find contributable candidates in a plausible and understandable search space, specified by a set of templates. We implemented the method as a tool, and our experimental evaluation showed that the tool was able to generate test suites for industrial implementation models with higher coverages and shorter execution times than Simulink Design Verifier. Additionally, the tool includes a fast coverage measurement engine, which demonstrated better performance than Simulink Coverage in our experiments.
ER -