Language Agnostic Code Embeddings

• URL: http://arxiv.org/abs/2310.16803v1
• Date: Wed, 25 Oct 2023 17:34:52 GMT
• Title: Language Agnostic Code Embeddings
• Authors: Saiteja Utpala, Alex Gu, Pin Yu Chen
• Abstract summary: We focus on the cross-lingual capabilities of code embeddings across different programming languages. Code embeddings comprise two distinct components: one deeply tied to the nuances and syntax of a specific language, and the other remaining agnostic to these details. We show that when we isolate and eliminate this language-specific component, we witness significant improvements in downstream code retrieval tasks.
• Score: 61.84835551549612
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recently, code language models have achieved notable advancements in addressing a diverse array of essential code comprehension and generation tasks. Yet, the field lacks a comprehensive deep dive and understanding of the code embeddings of multilingual code models. In this paper, we present a comprehensive study on multilingual code embeddings, focusing on the cross-lingual capabilities of these embeddings across different programming languages. Through probing experiments, we demonstrate that code embeddings comprise two distinct components: one deeply tied to the nuances and syntax of a specific language, and the other remaining agnostic to these details, primarily focusing on semantics. Further, we show that when we isolate and eliminate this language-specific component, we witness significant improvements in downstream code retrieval tasks, leading to an absolute increase of up to +17 in the Mean Reciprocal Rank (MRR).

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