2016 - ACM Distinguished Member
His primary scientific interests are in Distributed computing, Software, Debugging, Software bug and Data mining. His work focuses on many connections between Distributed computing and other disciplines, such as Reachability, that overlap with his field of interest in Software architecture, State and Static analysis. His work deals with themes such as Machine learning, Selection and Crash, which intersect with Software.
His Debugging study combines topics in areas such as Correctness, Bebugging and Fault detection and isolation. His Software bug study combines topics from a wide range of disciplines, such as Software maintenance and World Wide Web. Shing-Chi Cheung has researched Data mining in several fields, including Ubiquitous computing, Middleware and Context model.
Shing-Chi Cheung spends much of his time researching Software engineering, Distributed computing, Software, World Wide Web and Web service. His study in Software engineering is interdisciplinary in nature, drawing from both Java and Software design pattern. His Distributed computing research includes elements of Ubiquitous computing, Wireless sensor network, Correctness, Reachability and Software architecture.
The various areas that Shing-Chi Cheung examines in his Ubiquitous computing study include Middleware and Data mining. His study looks at the relationship between Software and topics such as Debugging, which overlap with Crash. His Web service research includes themes of Service, Workflow technology, Workflow and The Internet.
Shing-Chi Cheung focuses on Software engineering, Artificial intelligence, Software, Empirical research and Machine learning. His Software engineering research is multidisciplinary, incorporating elements of Software development, Class, Code, Java and Dependency. His Artificial intelligence research is multidisciplinary, relying on both Regular expression and Natural language processing.
His studies in Software integrate themes in fields like Set, Data mining and Benchmark. He conducts interdisciplinary study in the fields of Data mining and Computational semantics through his research. His Software bug research includes elements of Software maintenance, Sequence learning, Software evolution, Software metric and Sequence labeling.
Shing-Chi Cheung mainly investigates Software, Android, Compatibility, Software engineering and Debugging. His Software research is multidisciplinary, incorporating perspectives in Set, Machine learning, Data mining and Artificial intelligence. The Artificial intelligence study combines topics in areas such as Software bug, Software maintenance, Sequence labeling and Software evolution.
His work deals with themes such as Human–computer interaction, Static analysis and Data science, which intersect with Android. He interconnects Class, Dependency, Software debugging and Exploit in the investigation of issues within Software engineering. Shing-Chi Cheung integrates Debugging with Empirical research in his research.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
ReLink: recovering links between bugs and changes
Rongxin Wu;Hongyu Zhang;Sunghun Kim;Shing-Chi Cheung.
foundations of software engineering (2011)
Characterizing and detecting performance bugs for smartphone applications
Yepang Liu;Chang Xu;Shing-Chi Cheung.
international conference on software engineering (2014)
Taming coincidental correctness: Coverage refinement with context patterns to improve fault localization
Xinming Wang;S. C. Cheung;W. K. Chan;Zhenyu Zhang.
international conference on software engineering (2009)
Workflow View Driven Cross-Organizational Interoperability in a Web Service Environment
Dickson K. W. Chiu;S. C. Cheung;Sven Till;Kamalakar Karlapalem.
Information Technology & Management (2004)
Inconsistency detection and resolution for context-aware middleware support
Chang Xu;S. C. Cheung.
foundations of software engineering (2005)
Alerts in mobile healthcare applications: requirements and pilot study
E. Kafeza;D.K.W. Chiu;S.C. Cheung;M. Kafeza.
international conference of the ieee engineering in medicine and biology society (2004)
Metamorphic Testing: A New Approach for Generating Next Test Cases.
Tsong Yueh Chen;S. C. Cheung;Siu-Ming Yiu.
arXiv: Software Engineering (2020)
Context constraints for compositional reachability analysis
Shing Chi Cheung;Jeff Kramer.
ACM Transactions on Software Engineering and Methodology (1996)
Checking safety properties using compositional reachability analysis
Shing Chi Cheung;Jeff Kramer.
ACM Transactions on Software Engineering and Methodology (1999)
A Metamorphic Testing Approach for Online Testing of Service-Oriented Software Applications
W.K. Chan;Shing Chi Cheung;Karl R.P.H. Leung.
International Journal of Web Services Research (2007)
Profile was last updated on December 6th, 2021.
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