Authors:
Narumi Yoneda
;
Ryo Hatano
and
Hiroyuki Nishiyama
Affiliation:
Department of Industrial and Systems Engineering, Graduate School of Science and Technology, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba, Japan
Keyword(s):
Dynamic Analysis, System-Call Sequence, Code Translation, Natural Language Processing.
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.
(More)