STraceBERT: Source Code Retrieval using Semantic Application Traces

December 07, 2023 Β· Declared Dead Β· πŸ› ESEC/SIGSOFT FSE

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Authors Claudio Spiess arXiv ID 2312.04731 Category cs.SE: Software Engineering Cross-listed cs.AI, cs.IR Citations 0 Venue ESEC/SIGSOFT FSE Last Checked 3 months ago
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.
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