ArkTS-CodeSearch: 一个用于代码检索的开源ArkTS数据集
ArkTS-CodeSearch: A Open-Source ArkTS Dataset for Code Retrieval
AI总结：
本文提出一个开源ArkTS数据集，用于代码检索任务，通过微调模型提升ArkTS代码理解能力。
摘要：
ArkTS是OpenHarmony生态系统中的核心编程语言，然而关于ArkTS代码智能的研究受到公开数据集和评估基准不足的限制。本文提出一个大规模的ArkTS数据集，来源于开源仓库，旨在代码检索和代码评估任务。我们设计了一个单次检索任务，利用自然语言注释来检索相应的ArkTS函数。ArkTS仓库从GitHub和Gitee爬取，使用tree-sitter-arkts提取注释-函数对，随后进行跨平台去重和ArkTS函数类型的统计分析。我们进一步在单次检索任务上评估现有的开源代码嵌入模型，并使用ArkTS和TypeScript训练数据集进行微调，得到一个高性能的ArkTS代码理解模型。本工作建立了首个系统化的ArkTS代码检索基准。数据集和我们微调的模型可在https://huggingface.co/hreyulog/embedinggemma_arkts和https://huggingface.co/datasets/hreyulog/arkts-code-docstring获取。
英文摘要：
ArkTS is a core programming language in the OpenHarmony ecosystem, yet research on ArkTS code intelligence is hindered by the lack of public datasets and evaluation benchmarks. This paper presents a large-scale ArkTS dataset constructed from open-source repositories, targeting code retrieval and code evaluation tasks. We design a single-search task, where natural language comments are used to retrieve corresponding ArkTS functions. ArkTS repositories are crawled from GitHub and Gitee, and comment-function pairs are extracted using tree-sitter-arkts, followed by cross-platform deduplication and statistical analysis of ArkTS function types. We further evaluate existing open-source code embedding models on the single-search task and perform fine-tuning using both ArkTS and TypeScript training datasets, resulting in a high-performing model for ArkTS code understanding. This work establishes the first systematic benchmark for ArkTS code retrieval. Both the dataset and our fine-tuned model are available at https://huggingface.co/hreyulog/embedinggemma_arkts and https://huggingface.co/datasets/hreyulog/arkts-code-docstring .
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
