Neural Code Search Evaluation Dataset
arXiv:1908.09804
Abstract
There has been an increase of interest in code search using natural language. Assessing the performance of such code search models can be difficult without a readily available evaluation suite. In this paper, we present an evaluation dataset consisting of natural language query and code snippet pairs, with the hope that future work in this area can use this dataset as a common benchmark. We also provide the results of two code search models ([1] and [6]) from recent work. The evaluation dataset is available at https://github.com/facebookresearch/Neural-Code-Search-Evaluation-Dataset
Cited by in corpus (6)
- Deep Graph Matching and Searching for Semantic Code Retrieval
- On the Effectiveness of Transfer Learning for Code Search
- Survey of Code Search Based on Deep Learning
- Senatus -- A Fast and Accurate Code-to-Code Recommendation Engine
- CoSQA: 20,000+ Web Queries for Code Search and Question Answering
- Search4Code: Code Search Intent Classification Using Weak Supervision