DexBERT: Effective, task-agnostic and fine-grained representation learning of Android bytecode
The automation of an increasingly large number of software engineering tasks is becoming possible thanks to Machine Learning (ML). One foundational building block in the application of ML to software artifacts is the representation of these artifacts ( e.g. , source code or executable code) into a f...
Saved in:
Main Authors: | SUN, Tiezhu, ALLIX, Kevin, KIM, Kisub, ZHOU, Xin, KIM, Dongsun, LO, David, BISSYANDE, Tegawendé F., KLEIN, Jacques |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2023
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/8509 https://ink.library.smu.edu.sg/context/sis_research/article/9512/viewcontent/DexBERT_Effective_Task_Agnostic_and_Fine_Grained_Representation_Learning_of_Android_Bytecode.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
On locating malicious code in piggybacked Android apps
by: LI, Li, et al.
Published: (2017) -
Assessing the generalizability of code2vec token embeddings
by: KANG, Hong Jin, et al.
Published: (2019) -
Big Code Search: A Bibliography
by: KIM, Kisub, et al.
Published: (2024) -
Understanding Android app piggybacking: A systematic study of malicious code grafting
by: LI, Li, et al.
Published: (2017) -
GraphCode2Vec: Generic code embedding via lexical and program dependence analyses
by: MA, Wei, et al.
Published: (2022)