English

STraceBERT: Source Code Retrieval using Semantic Application Traces

Software Engineering 2023-12-11 v1 Artificial Intelligence Information Retrieval

Abstract

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.

Keywords

Cite

@article{arxiv.2312.04731,
  title  = {STraceBERT: Source Code Retrieval using Semantic Application Traces},
  author = {Claudio Spiess},
  journal= {arXiv preprint arXiv:2312.04731},
  year   = {2023}
}