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.
Predicting Faults from Cached History
2007368 citationsSunghun Kim, Thomas Zimmermann et al.Rare & Special e-Zone (The Hong Kong University of Science and Technology)profile →
ReLink
2011304 citationsRongxin Wu, Hongyu Zhang et al.Rare & Special e-Zone (The Hong Kong University of Science and Technology)profile →
Heterogeneous Defect Prediction
2017203 citationsJaechang Nam, Wei Fu et al.IEEE Transactions on Software Engineeringprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Sunghun Kim'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 Sunghun Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunghun Kim more than expected).
This network shows the impact of papers produced by Sunghun Kim. 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 Sunghun Kim. The network helps show where Sunghun Kim may publish in the future.
Co-authorship network of co-authors of Sunghun Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Sunghun Kim.
A scholar is included among the top collaborators of Sunghun Kim 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 Sunghun Kim. Sunghun Kim is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kim, Sunghun, et al.. (2019). An Analysis of Pre-Service Science Teachers’ PCK for Lessons Using Analogies. Journal of The Korean Association For Science Education. 39(3). 441–456.1 indexed citations
4.
Nam, Jaechang, Wei Fu, Sunghun Kim, Tim Menzies, & Lin Tan. (2017). Heterogeneous Defect Prediction. IEEE Transactions on Software Engineering. 44(9). 874–896.203 indexed citations breakdown →
5.
Lee, Sanghoon, Daniel M. Germán, Seung-won Hwang, & Sunghun Kim. (2015). Crowdsourcing Identification of License Violations. Journal of Computing Science and Engineering. 9(4). 190–203.1 indexed citations
Sadowski, Caitlin, Jaeheon Yi, & Sunghun Kim. (2012). The evolution of data races. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 171–174.2 indexed citations
Kim, Sunghun, et al.. (2010). OCAT. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 159–170.52 indexed citations
12.
Kim, Jin-Han, Sang-Hoon Lee, Seung-won Hwang, & Sunghun Kim. (2009). Adding Examples into Java Documents. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 540–544.31 indexed citations
Kim, Sunghun, Thomas Zimmermann, E. James Whitehead, & Andreas Zeller. (2007). Predicting Faults from Cached History. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 489–498.368 indexed citations breakdown →
15.
Kim, Sunghun & Michael D. Ernst. (2007). Which warnings should I fix first?. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 45–54.153 indexed citations
16.
Kim, Sunghun, et al.. (2006). Properties of Signature Change Patterns. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 8. 4–13.18 indexed citations
17.
Zimmermann, Thomas, Sunghun Kim, Andreas Zeller, & E. James Whitehead. (2006). Mining version archives for co-changed lines. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 72–75.48 indexed citations
18.
Pan, Kai, Sunghun Kim, & E. James Whitehead. (2006). Bug Classification Using Program Slicing Metrics. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 31–42.35 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.