mlsanityData to 7 Oct 2026

Opportunities and Challenges in Code Search Tools

arXiv 2011.02297 ↗First posted 4 Nov 2020cs.SEcited by 22

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Abstract (arXiv)

Code search is a core software engineering task. Effective code search tools can help developers substantially improve their software development efficiency and effectiveness. In recent years, many code search studies have leveraged different techniques, such as deep learning and information retrieval approaches, to retrieve expected code from a large-scale codebase. However, there is a lack of a comprehensive comparative summary of existing code search approaches. To understand the research trends in existing code search studies, we systematically reviewed 81 relevant studies. We investigated the publication trends of code search studies, analyzed key components, such as codebase, query, and modeling technique used to build code search tools, and classified existing tools into focusing on supporting seven different search tasks. Based on our findings, we identified a set of outstanding challenges in existing studies and a research roadmap for future code search research.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Nov 2020.

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Citing papers per year: 2021: 7; 2022: 5; 2023: 1; 2024: 2; 2025: 6; 2026: 1.

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  1. 2021CoSQA: 20,000+ Web Queries for Code Search and Question Answeringcited by 74
  2. 2022On the Importance of Building High-quality Training Datasets for Neural Code Searchcited by 30
  3. 2025What to Retrieve for Effective Retrieval-Augmented Code Generation? An Empirical Study and Beyondcited by 22
  4. 2022CoCoSoDa: Effective Contrastive Learning for Code Searchcited by 21
  5. 2025An Empirical Study of Retrieval-Augmented Code Generation: Challenges and Opportunitiescited by 17
  6. 2021GraphSearchNet: Enhancing GNNs via Capturing Global Dependencies for Semantic Code Searchcited by 15
  7. 2024Rocks Coding, Not Development--A Human-Centric, Experimental Evaluation of LLM-Supported SE Taskscited by 13
  8. 2021Multimodal Representation for Neural Code Searchcited by 11
  9. 2022Code Search based on Context-aware Code Translationcited by 11
  10. 2025Exploring the Security Threats of Knowledge Base Poisoning in Retrieval-Augmented Code Generationcited by 9
  11. 2022Exploring Representation-Level Augmentation for Code Searchcited by 8
  12. 2024LLM Agents Improve Semantic Code Searchcited by 7
10 more
  1. 2021Predicting Patch Correctness Based on the Similarity of Failing Test Casescited by 4
  2. 2022Towards Using Data-Influence Methods to Detect Noisy Samples in Source Code Corporacited by 4
  3. 2023Code Search Debiasing:Improve Search Results beyond Overall Ranking Performancecited by 4
  4. 2021AugmentedCode: Examining the Effects of Natural Language Resources in Code Retrieval Modelscited by 3
  5. 2021Senatus -- A Fast and Accurate Code-to-Code Recommendation Enginecited by 3
  6. 2021A Systematic Review of Automated Query Reformulations in Source Code Searchcited by 2
  7. 2025Zero-Shot Cross-Domain Code Search without Fine-Tuningcited by 2
  8. 2025LinkAnchor: An Autonomous LLM-Based Agent for Issue-to-Commit Link Recoverycited by 2
  9. 2025An Empirical Study of Knowledge Distillation for Code Understanding Taskscited by 2
  10. 2026XSearch: Explainable Code Search via Concept-to-Code Alignmentcited by 0