System-Call-Level Dynamic Analysis for Code Translation Candidate Selection

Narumi Yoneda, Ryo Hatano, Hiroyuki Nishiyama

2024

Abstract

In this study, we propose a methodology that uses dynamic analysis (DA) data to select better code-translation candidates. For the DA data, we recorded the history of system-call invocations to understand the actions of the program during execution, providing insights independent of the programming language. We implemented and publicized a DA system, which enabled a fully automated analysis. In our method, we generated multiple translation candidates for programming languages using TransCoder. Subsequently, we performed DA on all the generated candidates and original code. For optimal selection, we compared the DA data of the original code with the generated data and calculated the similarity. To compare the DA data, we used natural language processing techniques on DA data to fix the sequence length. We also attempted to directly compare the variable-length system-call sequences. In this study, we demonstrated that the characteristics of system-call invocations vary even within the same code. For instance, the order of invocations and the number of times the same system-calls an invocation differ. We discuss the elimination of these uncertainties when comparing system-calls.

Paper Citation

in Harvard Style

Yoneda N., Hatano R. and Nishiyama H. (2024). System-Call-Level Dynamic Analysis for Code Translation Candidate Selection. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4, SciTePress, pages 576-583. DOI: 10.5220/0012372900003636

in Bibtex Style

@conference{icaart24,
author={Narumi Yoneda and Ryo Hatano and Hiroyuki Nishiyama},
title={System-Call-Level Dynamic Analysis for Code Translation Candidate Selection},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={576-583},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012372900003636},
isbn={978-989-758-680-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - System-Call-Level Dynamic Analysis for Code Translation Candidate Selection
SN - 978-989-758-680-4
AU - Yoneda N.
AU - Hatano R.
AU - Nishiyama H.
PY - 2024
SP - 576
EP - 583
DO - 10.5220/0012372900003636
PB - SciTePress