NBSearch：计算笔记本的语义搜索和可视化探索
NBSearch: Semantic Search and Visual Exploration of Computational Notebooks
摘要：
代码搜索对于使用计算笔记本（例如，yter）。笔记本的灵活性为有效的代码搜索带来了挑战，传统软件代码的经典搜索界面可能受到限制。在本文中，我们提出，NBSearch，一个新的系统，支持语义代码搜索笔记本收藏和交互式视觉探索的搜索结果。NBSearch利用先进的机器学习模型来支持自然语言搜索查询和直观的可视化，以在返回的结果中呈现复杂的笔记本内部和笔记本之间的关系。我们通过一个迭代的参与式设计过程与来自一家大型软件公司的两位专家一起开发了NBSearch。我们通过一系列实验对模型进行了评估，并通过受控用户研究对整个系统进行了评估。结果表明，我们的分析管道的可行性和NBSearch的有效性，以支持大型笔记本电脑集合中的代码搜索。
英文摘要：
Code search is an important and frequent activity for developers using computational notebooks (e.g., Jupyter). The flexibility of notebooks brings challenges for effective code search, where classic search interfaces for traditional software code may be limited. In this paper, we propose, NBSearch, a novel system that supports semantic code search in notebook collections and interactive visual exploration of search results. NBSearch leverages advanced machine learning models to enable natural language search queries and intuitive visualizations to present complicated intra- and inter-notebook relationships in the returned results. We developed NBSearch through an iterative participatory design process with two experts from a large software company. We evaluated the models with a series of experiments and the whole system with a controlled user study. The results indicate the feasibility of our analytical pipeline and the effectiveness of NBSearch to support code search in large notebook collections.
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。
