Searching a Database of Source Codes Using Contextualized Code Search

Summary: Contextualized code search uses partial code and surrounding context to surface database code for completion. Neural predictor paired with a reverse encoder enables fast scoring of candidates via a convolution of two Gaussians, enabling scalable search over large codebases. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12078
Venue: VLDB
Year: 2020
Pagerank: 4.3177432e-05
Overall Rank: 9,610 | 33.15%
DOI: 10.14778/3401960.3401972

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,628	CatDB: Data-catalog-guided, LLM-based Generation of Data-centric ML Pipelines	2025	VLDB	4.1945683e-05

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank

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