Comparing Code Similarity Using Information Retrieval Techniques and Deep Learning

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  • 情報検索技術と深層学習を用いたコード片類似性判定法の比較調査

Abstract

Measuring code similarity is a fundamental technique in software engineering. It is challenging to measure code similarity not only syntactical but also functional. Previous research proposed measuring functional similarity using information retrieval (IR) techniques. Recently, measurement methods using deep learning have also been proposed. They have different pros and cons in terms of accuracy and calculation time. In this paper, we compare the combination of IR and deep learning for code similarity. As a result, the combination of LSI (Latent Semantic Indexing), a sort of IR technique, and a deep learning model showed the highest accuracy and fastest calculation time.

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