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20182023
most citedChallenging Machine Learning-based Clone Detectors via Semantic-preserving Code Transformations

46 citations · 117 across the 12 of their papers we have counts for

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5 papers · 1 filter

cs.SE2023

Eunomia: Enabling User-specified Fine-Grained Search in Symbolically Executing WebAssembly Binaries

Ningyu He, Zhehao Zhao, Jikai Wang +7

Although existing techniques have proposed automated approaches to alleviate the path explosion problem of symbolic execution, users still need to optimize symbolic execution by ap…

cs.SE2022★ 6 cited

A Survey on Automated Driving System Testing: Landscapes and Trends

Shuncheng Tang, Zhenya Zhang, Yi Zhang +8

Automated Driving Systems (ADS) have made great achievements in recent years thanks to the efforts from both academia and industry. A typical ADS is composed of multiple modules, i…

cs.SE2021★ 46 cited

Challenging Machine Learning-based Clone Detectors via Semantic-preserving Code Transformations

Weiwei Zhang, Shengjian Guo, Hongyu Zhang +3

Software clone detection identifies similar code snippets. It has been an active research topic that attracts extensive attention over the last two decades. In recent years, machin…

cs.SE2020★ 18 cited

MUZZ: Thread-aware Grey-box Fuzzing for Effective Bug Hunting in Multithreaded Programs

Hongxu Chen, Shengjian Guo, Yinxing Xue +5

Grey-box fuzz testing has revealed thousands of vulnerabilities in real-world software owing to its lightweight instrumentation, fast coverage feedback, and dynamic adjusting strat…

cs.SE2019★ 4 cited

SAVIOR: Towards Bug-Driven Hybrid Testing

Yaohui Chen, Peng Li, Jun Xu +5

Hybrid testing combines fuzz testing and concolic execution. It leverages fuzz testing to test easy-to-reach code regions and uses concolic execution to explore code blocks guarded…