Sang Kil

3.0k citations
42 papers · 1.7k indexed · 1 hit paper · h-index 19
Topics
Software Testing and Debugging Techniques (27 papers)Advanced Malware Detection Techniques (24 papers)Software Engineering Research (12 papers)

In The Last Decade

Sang Kil

37 papers receiving 1.7k citations

Hit Papers

Unleashing Mayhem on Binary Code20122026201620212012100200300

Peers

Sang Kil
Comparison fields: 5 of 59
  • Software 1.1k
  • Signal Processing 1.1k
  • Information Systems 754
  • Artificial Intelligence 616
  • Computer Networks and Communications 308
Replace Yan Shoshitaishvili with:
Yan Shoshitaishvili United States
Işıl Dillig United States
Yinxing Xue China
Abdelwahab Hamou‐Lhadj Canada
Clark Thomborson New Zealand
Daya Guo China
Martin Monperrus Sweden
Guozhu Meng China
Joshua Garcia United States
Hamid Bagheri United States
Sang Kil relative to Yan Shoshitaishvili United States Yan Shoshitaishvili's profile →
Citations per field
00.5×1.6×
Yan Shoshitaishvili · 1×
Citations per year

Countries citing papers authored by Sang Kil

Since Specialization
Citations

This map shows the geographic impact of Sang Kil'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 Sang Kil with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sang Kil more than expected).

Fields of papers citing papers by Sang Kil

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sang Kil. 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 Sang Kil. The network helps show where Sang Kil may publish in the future.

Co-authorship network of co-authors of Sang Kil

This figure shows the co-authorship network connecting the top 25 collaborators of Sang Kil. A scholar is included among the top collaborators of Sang Kil 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 Sang Kil. Sang Kil is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 0
4 1
5 1
6 52
7 105
8
Montage: A Neural Network Language Model-Guided JavaScript Engine Fuzzer
1
9 37
10 50
11
Fuzzing: Art, Science, and Engineering.
18
12
Git-based {CTF}: A Simple and Effective Approach to Organizing In-Course Attack-and-Defense Security Competition
7
13 67
14 56
15 13
16 4
17 42
18 9
19 26
20
Investigation on the Corrosion Behaviour of Weld Structure
4

About Sang Kil

Sang Kil is a scholar working on Software, Signal Processing and Hardware and Architecture, having authored 42 papers that have together received 1.7k indexed citations. Recurring topics across this work include Software Testing and Debugging Techniques (27 papers), Advanced Malware Detection Techniques (24 papers) and Software Engineering Research (12 papers). The work is most often cited by research in Software (1.1k citations), Signal Processing (1.1k citations) and Information Systems (754 citations). Sang Kil has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include David Brumley, Thanassis Avgerinos, Maverick Woo, Hyung-Seok Han, Soomin Kim, Edward J. Schwartz, Gustavo Grieco, Marcel Böhme, Alex Groce and Iulian Moraru. Their work appears in journals such as Communications of the ACM, IEEE Transactions on Software Engineering and Computers & Security.

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.

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