Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
An orchestrated survey of methodologies for automated software test case generation
Countries citing papers authored by Tsong Yueh Chen
Since
Specialization
Citations
This map shows the geographic impact of Tsong Yueh Chen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tsong Yueh Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tsong Yueh Chen more than expected).
This network shows the impact of papers produced by Tsong Yueh Chen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tsong Yueh Chen. The network helps show where Tsong Yueh Chen may publish in the future.
Co-authorship network of co-authors of Tsong Yueh Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Tsong Yueh Chen.
A scholar is included among the top collaborators of Tsong Yueh Chen based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Tsong Yueh Chen. Tsong Yueh Chen is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhang, Xiaofang, Tsong Yueh Chen, & Huai Liu. (2014). An application of Adaptive Random Sequence in test case prioritization. Swinburne Research Bank (Swinburne University of Technology). 126–131.12 indexed citations
10.
Jiang, Mingyue, Tsong Yueh Chen, Fei‐Ching Kuo, Zhi Quan Zhou, & Zuohua Ding. (2014). Testing model transformation programs using metamorphic testing. Swinburne Research Bank (Swinburne University of Technology). 94–99.8 indexed citations
Chan, Kwok Ping, Tsong Yueh Chen, & Dave Towey. (2005). Adaptive Random Testing with Filtering: An Overhead Reduction Technique. Software Engineering and Knowledge Engineering. 292–299.8 indexed citations
13.
Chen, Tsong Yueh, Fei‐Ching Kuo, & Robert Merkel. (2004). On the statistical properties of the F-measure. Swinburne Research Bank (Swinburne University of Technology). 146–153.43 indexed citations
14.
Chen, Tsong Yueh, et al.. (2004). An Empirical Evaluation and Analysis of the Fault-Detection Capability of MUMCUT for General Boolean Expressions * +. Swinburne Research Bank (Swinburne University of Technology).4 indexed citations
15.
Chen, Tsong Yueh, et al.. (2004). Case studies on the selection of useful relations in metamorphic testing. Swinburne Research Bank (Swinburne University of Technology).87 indexed citations
Cain, Andrew, et al.. (2003). ADDICT : a prototype system for automated test data generation using the integrated classification-tree methodology. Swinburne Research Bank (Swinburne University of Technology). 76.2 indexed citations
18.
Cain, Andrew, et al.. (2003). Runtime Data Analysis for Java Programs. Swinburne Research Bank (Swinburne University of Technology).6 indexed citations
19.
Chen, Tsong Yueh, et al.. (2000). Analysing the category-partition method and the classification-tree method for software testing. Swinburne Research Bank (Swinburne University of Technology).1 indexed citations
20.
Chen, Tsong Yueh, et al.. (1998). Application of metamorphic testing in numerical analysis. Rare & Special e-Zone (The Hong Kong University of Science and Technology).35 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.