activity
20202022
most citedDetecting False Alarms from Automatic Static Analysis Tools: How Far are We?

45 citations · 110 across the 9 of their papers we have counts for

collaborators

12 papers

cs.SE20225 cited

SkipFuzz: Active Learning-based Input Selection for Fuzzing Deep Learning Libraries

Hong Jin Kang, Pattarakrit Rattanukul, Stefanus Agus Haryono +4

Many modern software systems are enabled by deep learning libraries such as TensorFlow and PyTorch. As deep learning is now prevalent, the security of deep learning libraries is a…

cs.CR2022

VulCurator: A Vulnerability-Fixing Commit Detector

Truong Giang Nguyen, Thanh Le-Cong, Hong Jin Kang +2

Open-source software (OSS) vulnerability management process is important nowadays, as the number of discovered OSS vulnerabilities is increasing over time. Monitoring vulnerability…

cs.SE202220 cited

AutoPruner: Transformer-Based Call Graph Pruning

Thanh Le-Cong, Hong Jin Kang, Truong Giang Nguyen +4

Constructing a static call graph requires trade-offs between soundness and precision. Program analysis techniques for constructing call graphs are unfortunately usually imprecise.…

cs.SE2022

Compressing Pre-trained Models of Code into 3 MB

Jieke Shi, Zhou Yang, Bowen Xu +2

Although large pre-trained models of code have delivered significant advancements in various code processing tasks, there is an impediment to the wide and fluent adoption of these…

cs.SE202225 cited

Active Learning of Discriminative Subgraph Patterns for API Misuse Detection

Hong Jin Kang, David Lo

A common cause of bugs and vulnerabilities are the violations of usage constraints associated with Application Programming Interfaces (APIs). API misuses are common in software pro…

cs.SE202245 cited

Detecting False Alarms from Automatic Static Analysis Tools: How Far are We?

Hong Jin Kang, Khai Loong Aw, David Lo

Automatic static analysis tools (ASATs), such as Findbugs, have a high false alarm rate. The large number of false alarms produced poses a barrier to adoption. Researchers have pro…