STraceBERT: Source Code Retrieval using Semantic Application Traces
–arXiv.org Artificial Intelligence
Software reverse engineering is an essential task in software engineering and security, but it can be a challenging process, especially for adversarial artifacts. To address this challenge, we present STraceBERT, a novel approach that utilizes a Java dynamic analysis tool to record calls to core Java libraries, and pretrain a BERT-style model on the recorded application traces for effective method source code retrieval from a candidate set. Our experiments demonstrate the effectiveness of STraceBERT in retrieving the source code compared to existing approaches. Our proposed approach offers a promising solution to the problem of code retrieval in software reverse engineering and opens up new avenues for further research in this area.
arXiv.org Artificial Intelligence
Dec-7-2023
- Country:
- North America > United States > California (0.15)
- Genre:
- Research Report > Promising Solution (0.54)
- Industry:
- Information Technology > Security & Privacy (0.47)
- Technology: