computer-code-11

Annotated Code Search

3260 papers • 126 benchmarks • 313 datasets

Annotated code search is the retrieval of code snippets paired with brief descriptions of their intent using natural language queries.

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in annotated-code-search-11

Trend

Dataset

Best Model

Actions

PACS-StaQC-py

PACS-SO-DS

PACS-CoNaLa

Libraries

i

Use these libraries to find annotated-code-search-11 models and implementations

Datasets

PACS

PyTorrent

ISAdetect dataset

Subtasks

No subtasks available.

Most implemented papers

Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction

Ted Briscoe, Christopher Bryant, Mariano Felice•Fri Jun 30 2017

ERRANT, a grammatical ERRor ANnotation Toolkit designed to automatically extract edits from parallel original and corrected sentences and classify them according to a new, dataset-agnostic, rule-based framework, which facilitates error type evaluation at different levels of granularity.

345

Content

0

Paper Graph

Neural Code Search Revisited: Enhancing Code Snippet Retrieval through Natural Language Intent

Geert Heyman, T. V. Cutsem•Wed Aug 26 2020

A domain-specific retrieval model for code annotated with a natural language description is created that yields significantly more relevant search results compared to state-of-the-art code retrieval methods that do not use descriptions.

34 0

Paper Graph

Adding a benchmark result helps the community track progress.