Papers Code Search
“Code Search” 태그가 달린 논문 147편 · 필터 해제
How Small Transformation Expose the Weakness of Semantic Similarity Measures
This research examines how well different methods measure semantic similarity, which is important for various software engineering applications such as code search, API recommendations, automated code reviews, and refact…
Semantic SimilarityCode SearchThe Impact of LLM-Assistants on Software Developer Productivity: A Systematic Review and Mapping Study
Large language model assistants (LLM-assistants) present new opportunities to transform software development. Developers are increasingly adopting these tools across tasks, including coding, testing, debugging, documenta…
Code SearchMGS3: A Multi-Granularity Self-Supervised Code Search Framework
In the pursuit of enhancing software reusability and developer productivity, code search has emerged as a key area, aimed at retrieving code snippets relevant to functionalities based on natural language queries. Despite…
Code SearchContrastive LearningNatural Language QueriesDeepRTL2: A Versatile Model for RTL-Related Tasks
The integration of large language models (LLMs) into electronic design automation (EDA) has significantly advanced the field, offering transformative benefits, particularly in register transfer level (RTL) code generatio…
Code GenerationCode SearchKnowledge Graph Based Repository-Level Code Generation
Recent advancements in Large Language Models (LLMs) have transformed code generation from natural language queries. However, despite their extensive knowledge and ability to produce high-quality code, LLMs often struggle…
Code GenerationCode SearchNatural Language QueriesRetrievalLEANCODE: Understanding Models Better for Code Simplification of Pre-trained Large Language Models
Large Language Models for code often entail significant computational complexity, which grows significantly with the length of the input code sequence. We propose LeanCode for code simplification to reduce training and p…
Code SearchCode SummarizationDecoderLarge Language Models are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks
Pre-trained code models rely heavily on high-quality pre-training data, particularly human-written reference comments that bridge code and natural language. However, these comments often become outdated as software evolv…
Code SearchCode SummarizationTowards Leveraging Large Language Model Summaries for Topic Modeling in Source Code
Understanding source code is a topic of great interest in the software engineering community, since it can help programmers in various tasks such as software maintenance and reuse. Recent advances in large language model…
Code SearchLanguage ModelingLanguage ModellingLarge Language ModelA Study on Mixup-Inspired Augmentation Methods for Software Vulnerability Detection
Various deep learning (DL) methods have recently been utilized to detect software vulnerabilities. Real-world software vulnerability datasets are rare and hard to acquire, as there is no simple metric for classifying vul…
Code SearchVulnerability DetectionZero-Shot Cross-Domain Code Search without Fine-Tuning
Code search aims to retrieve semantically relevant code snippets for natural language queries. While pre-trained language models (PLMs) have shown remarkable performance in this task, they struggle in cross-domain scenar…
Code SearchNatural Language QueriesOASIS: Order-Augmented Strategy for Improved Code Search
Code embeddings capture the semantic representations of code and are crucial for various code-related large language model (LLM) applications, such as code search. Previous training primarily relies on optimizing the Inf…
Code SearchLanguage ModelingLanguage ModellingLarge Language ModelLoRACode: LoRA Adapters for Code Embeddings
Code embeddings are essential for semantic code search; however, current approaches often struggle to capture the precise syntactic and contextual nuances inherent in code. Open-source models such as CodeBERT and UniXcod…
Code Searchparameter-efficient fine-tuningRetrievalMoSE: Hierarchical Self-Distillation Enhances Early Layer Embeddings
Deploying language models often requires navigating accuracy vs. performance trade-offs to meet latency constraints while preserving utility. Traditional model distillation reduces size but incurs substantial costs throu…
AllCode SearchCode TranslationRetrievalBeyond Natural Language Perplexity: Detecting Dead Code Poisoning in Code Generation Datasets
The increasing adoption of large language models (LLMs) for code-related tasks has raised concerns about the security of their training datasets. One critical threat is dead code poisoning, where syntactically valid but …
Code GenerationCode SearchURECA: The Chain of Two Minimum Set Cover Problems exists behind Adaptation to Shifts in Semantic Code Search
Adaptation is to make model learn the patterns shifted from the training distribution. In general, this adaptation is formulated as the minimum entropy problem. However, the minimum entropy problem has inherent limitatio…
ClusteringCode SearchRepository-level Code Search with Neural Retrieval Methods
This paper presents a multi-stage reranking system for repository-level code search, which leverages the vastly available commit histories of large open-source repositories to aid in bug fixing. We define the task of rep…
Bug fixingCode SearchRerankingRetrievalOrcaLoca: An LLM Agent Framework for Software Issue Localization
Recent developments in Large Language Model (LLM) agents are revolutionizing Autonomous Software Engineering (ASE), enabling automated coding, problem fixes, and feature improvements. However, localization -- precisely i…
Code SearchLanguage ModelingLanguage ModellingLarge Language Model+1On the Compression of Language Models for Code: An Empirical Study on CodeBERT
Language models have proven successful across a wide range of software engineering tasks, but their significant computational costs often hinder their practical adoption. To address this challenge, researchers have begun…
Code SearchCode SummarizationKnowledge DistillationQuantization+1Isotropy Matters: Soft-ZCA Whitening of Embeddings for Semantic Code Search
Low isotropy in an embedding space impairs performance on tasks involving semantic inference. Our study investigates the impact of isotropy on semantic code search performance and explores post-processing techniques to m…
Code SearchCodeSAM: Source Code Representation Learning by Infusing Self-Attention with Multi-Code-View Graphs
Machine Learning (ML) for software engineering (SE) has gained prominence due to its ability to significantly enhance the performance of various SE applications. This progress is largely attributed to the development of …
Clone DetectionCode SearchRepresentation LearningSmall Language Model