Mar 21, 2018 · In this paper, we focus on improving fault localization of Simulink models by generating test cases. We identify four test objectives that aim ...

(4) We study the impact of changing the threshold value used to label training data for prediction models on the trade-off between fault localization accuracy ...

In this paper, we focus on improving fault localization of Simulink models by generating test cases. We identify four test objectives that aim to increase test ...

Effective fault localization of automotive Simulink models: achieving the trade-off between test oracle effort and fault localization accuracy · Bing Liu, S.

Abstract One promising way to improve the accuracy of fault localization based on statistical debugging is to increase diversity among test cases in the ...

Abstract. One promising way to improve the accuracy of fault localization based on statistical debugging is to increase diversity among test cases in the ...

In this paper, we focus on improving fault localization of Simulink models by generating test cases. We identify four test objectives that aim to increase test ...

Effective fault localization of automotive Simulink models: achieving the trade-off between test oracle effort and fault localization accuracy. · Liu, Bing; ...

One promising way to improve the accuracy of fault localization based on statistical debugging is to increase diversity among test cases in the underlying ...

TL;DR: A prediction model is developed to help stop test generation when adding test cases is unlikely to improve fault localization and is able to maintain ...