What is he best known for?
The fields of study he is best known for:
- Programming language
- Artificial intelligence
- Operating system
His primary areas of investigation include Test case, Metamorphic testing, Algorithm, Random testing and Software testing.
Tsong Yueh Chen has researched Test case in several fields, including System testing, Software, Theoretical computer science and White-box testing.
His White-box testing research includes themes of Reliability engineering, Software performance testing and Software selection.
The various areas that Tsong Yueh Chen examines in his Metamorphic testing study include Machine learning, Correctness, Software quality and Oracle.
His Algorithm study combines topics from a wide range of disciplines, such as Statement, Expected value, Observational equivalence and Spectrum.
His research integrates issues of Sampling, Orthogonal array testing, Partition and Risk-based testing in his study of Random testing.
His most cited work include:
- An orchestrated survey of methodologies for automated software test case generation (388 citations)
- Adaptive random testing (303 citations)
- Adaptive Random Testing: The ART of test case diversity (243 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Test case, Random testing, Metamorphic testing, Software and Algorithm.
His Test case research is multidisciplinary, incorporating elements of Domain, Reliability engineering, Data mining and White-box testing.
Tsong Yueh Chen works mostly in the field of Random testing, limiting it down to concerns involving Orthogonal array testing and, occasionally, Functional testing.
His studies deal with areas such as Machine learning, Correctness, Oracle and Artificial intelligence as well as Metamorphic testing.
His work in Software covers topics such as Software engineering which are related to areas like Software construction and Database.
His Algorithm research is multidisciplinary, relying on both Theoretical computer science, Mathematical optimization and Spectrum.
He most often published in these fields:
- Test case (41.12%)
- Random testing (29.93%)
- Metamorphic testing (25.99%)
What were the highlights of his more recent work (between 2017-2021)?
- Metamorphic testing (25.99%)
- Software (25.00%)
- Data mining (19.74%)
In recent papers he was focusing on the following fields of study:
Tsong Yueh Chen spends much of his time researching Metamorphic testing, Software, Data mining, Test case and Artificial intelligence.
Tsong Yueh Chen interconnects Software bug, Relation and Oracle in the investigation of issues within Metamorphic testing.
His biological study spans a wide range of topics, including Visualization and Software engineering.
His studies in Data mining integrate themes in fields like Domain, Random testing and Code coverage.
Test case is a primary field of his research addressed under Test.
His Artificial intelligence study incorporates themes from Machine learning and Pattern recognition.
Between 2017 and 2021, his most popular works were:
- Metamorphic Testing: A Review of Challenges and Opportunities (224 citations)
- Metamorphic Testing: A New Approach for Generating Next Test Cases. (105 citations)
- Test case prioritization for object-oriented software: An adaptive random sequence approach based on clustering (23 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Artificial intelligence
- Operating system
Tsong Yueh Chen mostly deals with Metamorphic testing, Software, Software engineering, Test case and Software testing.
His Metamorphic testing research includes elements of Software bug and Relation.
His Software study combines topics in areas such as Empirical research, Data mining and Artificial intelligence.
His research in Artificial intelligence tackles topics such as Machine learning which are related to areas like Set, Test, Code coverage and Scheduling.
The concepts of his Software engineering study are interwoven with issues in Business Process Execution Language, Web service and Service.
His Software testing research incorporates elements of Classifier, Visualization and Random forest.
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