# Code Search: A Survey of Techniques for Finding Code

arXiv: https://arxiv.org/abs/2204.02765 · HTML: https://mlsanity.com/paper/2204.02765/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Apr 2022.

## Built on by (most cited first, 18 of 18)

- [RepairAgent: An Autonomous, LLM-Based Agent for Program Repair](https://mlsanity.com/paper/2403.17134/) (2024)
- [The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation](https://mlsanity.com/paper/2305.06156/) (2023)
- [Rethinking Negative Pairs in Code Search](https://mlsanity.com/paper/2310.08069/) (2023)
- [CoSQA+: Pioneering the Multi-Choice Code Search Benchmark with Test-Driven Agents](https://mlsanity.com/paper/2406.11589/) (2024)
- [GrepSeek: Training Search Agents for Direct Corpus Interaction](https://mlsanity.com/paper/2605.29307/) (2026)
- [CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval](https://mlsanity.com/paper/2506.11066/) (2025)
- [ContextCov: Deriving and Enforcing Executable Constraints from Agent Instruction Files](https://mlsanity.com/paper/2603.00822/) (2026)
- [Code Search Debiasing:Improve Search Results beyond Overall Ranking Performance](https://mlsanity.com/paper/2311.14901/) (2023)
- [Knowledge Graph Based Repository-Level Code Generation](https://mlsanity.com/paper/2505.14394/) (2025)
- [REINFOREST: Reinforcing Semantic Code Similarity for Cross-Lingual Code Search Models](https://mlsanity.com/paper/2305.03843/) (2023)
- [DocChecker: Bootstrapping Code Large Language Model for Detecting and Resolving Code-Comment Inconsistencies](https://mlsanity.com/paper/2306.06347/) (2023)
- [Fully Autonomous Programming using Iterative Multi-Agent Debugging with Large Language Models](https://mlsanity.com/paper/2503.07693/) (2025)
- [OASIS: Order-Augmented Strategy for Improved Code Search](https://mlsanity.com/paper/2503.08161/) (2025)
- [Neurosymbolic Repo-level Code Localization](https://mlsanity.com/paper/2604.16021/) (2026)
- [CSSAM:Code Search via Attention Matching of Code Semantics and Structures](https://mlsanity.com/paper/2208.03922/) (2022)
- [CodeScholar: Growing Idiomatic Code Examples](https://mlsanity.com/paper/2312.15157/) (2023)
- [XSearch: Explainable Code Search via Concept-to-Code Alignment](https://mlsanity.com/paper/2605.16046/) (2026)
- [SynH-Rank: Quality-Aware Code Search via Diverse Data Synthesis and Hierarchical Ranking Training](https://mlsanity.com/paper/2607.17139/) (2026)

## Abstract (arXiv)

The immense amounts of source code provide ample challenges and opportunities during software development. To handle the size of code bases, developers commonly search for code, e.g., when trying to find where a particular feature is implemented or when looking for code examples to reuse. To support developers in finding relevant code, various code search engines have been proposed. This article surveys 30 years of research on code search, giving a comprehensive overview of challenges and techniques that address them. We discuss the kinds of queries that code search engines support, how to preprocess and expand queries, different techniques for indexing and retrieving code, and ways to rank and prune search results. Moreover, we describe empirical studies of code search in practice. Based on the discussion of prior work, we conclude the article with an outline of challenges and opportunities to be addressed in the future.