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Code search is an important task that has seen many developments in recentyears. However, previous attempts have mostly considered the problem ofsearching for code by a text query. We argue that using a code snippet (andpossibly an associated traceback) as a query and looking for answers withbugfixing instructions and code samples is a natural use case that is notcovered by existing approaches. Moreover, existing datasets use commentsextracted from code rather than full-text descriptions as text, making themunsuitable for this use case. We present a new SearchBySnippet datasetimplementing the search-by-code use case based on StackOverflow data; it turnsout that in this setting, existing architectures fall short of the simplestBM25 baseline even after fine-tuning. We present a new single encoder modelSnippeR that outperforms several strong baselines on the SearchBySnippetdataset with a result of 0.451 Recall@10; we propose the SearchBySnippetdataset and SnippeR as a new important benchmark for code search evaluation.

Searching by Code: a New SearchBySnippet Dataset and SnippeR Retrieval Model for Searching by Code Snippets