Out of sight, out of mind: Better automatic vulnerability repair by broadening input ranges and sources

The advances of deep learning (DL) have paved the way for automatic software vulnerability repair approaches, which effectively learn the mapping from the vulnerable code to the fixed code. Nevertheless, existing DL-based vulnerability repair methods face notable limitations: 1) they struggle to han...

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Bibliographic Details
Main Authors: ZHOU, Xin, KIM, Kisub, XU, Bowen, HAN, DongGyun, LO, David
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2024
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Online Access:https://ink.library.smu.edu.sg/sis_research/9248
https://ink.library.smu.edu.sg/context/sis_research/article/10248/viewcontent/3597503.3639222.pdf
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Institution: Singapore Management University
Language: English