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Yihao Li
Researcher at Graz University of Technology
Publications - 31
Citations - 1449
Yihao Li is an academic researcher from Graz University of Technology. The author has contributed to research in topics: Computer science & Ontology (information science). The author has an hindex of 8, co-authored 16 publications receiving 941 citations. Previous affiliations of Yihao Li include University of Texas at Dallas.
Papers
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Journal ArticleDOI
A Survey on Software Fault Localization
TL;DR: A comprehensive overview of a broad spectrum of fault localization techniques, each of which aims to streamline the fault localization process and make it more effective by attacking the problem in a unique way is provided.
Journal ArticleDOI
The DStar Method for Effective Software Fault Localization
TL;DR: A technique named DStar (D*) is proposed which can suggest suspicious locations for fault localization automatically without requiring any prior information on program structure or semantics and is found to be more effective at locating faults than all the other techniques it is compared to.
Proceedings ArticleDOI
Software Fault Localization Using DStar (D
TL;DR: A technique named DStar (D*), which has its origins rooted in similarity coefficient-based analysis, is proposed, which can identify suspicious locations for fault localization automatically without requiring any prior information on program structure or semantics.
Journal ArticleDOI
Ontology-based test generation for automated and autonomous driving functions
Yihao Li,Jianbo Tao,Franz Wotawa +2 more
TL;DR: The proposed approach for testing autonomous driving takes ontologies describing the environment of autonomous vehicles, and automatically converts it to test cases that are used in a simulation environment to verify automated driving functions, and relies on combinatorial testing.
Proceedings ArticleDOI
Using Ontologies for Test Suites Generation for Automated and Autonomous Driving Functions
TL;DR: The general approach making use of ontologies of environment the system under test is interacting with is outlined including its potential for automation in the automotive domain where there is growing need for sophisticated verification based on simulation in case of automated and autonomous vehicles.