Papers Clone Detection
“Clone Detection” 태그가 달린 논문 68편 · 필터 해제
AST-Enhanced or AST-Overloaded? The Surprising Impact of Hybrid Graph Representations on Code Clone Detection
As one of the most detrimental code smells, code clones significantly increase software maintenance costs and heighten vulnerability risks, making their detection a critical challenge in software engineering. Abstract Sy…
Clone DetectionGraph AttentionGraph Neural NetworkGradient-Based Model Fingerprinting for LLM Similarity Detection and Family Classification
As Large Language Models (LLMs) become integral software components in modern applications, unauthorized model derivations through fine-tuning, merging, and redistribution have emerged as critical software engineering ch…
Clone DetectionClusteringCodeSSM: Towards State Space Models for Code Understanding
Although transformers are widely used for various code-specific tasks, they have some significant limitations. In this paper, we investigate State Space Models (SSMs) as a potential alternative to transformers for code u…
Clone DetectionLanguage ModelingLanguage ModellingMasked Language Modeling+3Should Code Models Learn Pedagogically? A Preliminary Evaluation of Curriculum Learning for Real-World Software Engineering Tasks
Learning-based techniques, especially advanced pre-trained models for code have demonstrated capabilities in code understanding and generation, solving diverse software engineering (SE) tasks. Despite the promising resul…
Clone DetectionCode SummarizationIncremental LearningTowards Secure AI-driven Industrial Metaverse with NFT Digital Twins
The rise of the industrial metaverse has brought digital twins (DTs) to the forefront. Blockchain-powered non-fungible tokens (NFTs) offer a decentralized approach to creating and owning these cloneable DTs. However, the…
Clone DetectionOn the Use of Deep Learning Models for Semantic Clone Detection
Detecting and tracking code clones can ease various software development and maintenance tasks when changes in a code fragment should be propagated over all its copies. Several deep learning-based clone detection models …
Clone DetectionDeep LearningCodeSAM: 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 ModelIn-Context Code-Text Learning for Bimodal Software Engineering
Bimodal software analysis initially appeared to be within reach with the advent of large language models. Unfortunately, the complex interplay of natural language text and code in software engineering, presents unique ch…
Clone DetectionIn-Context LearningProgram RepairPrompt Learning+1An Effective Approach to Embedding Source Code by Combining Large Language and Sentence Embedding Models
The advent of large language models (LLMs) has significantly advanced artificial intelligence (AI) in software engineering (SE), with source code embeddings playing a crucial role in tasks such as source code clone detec…
Clone DetectionDomain AdaptationSentenceSentence Embedding+2Augmenting the Interpretability of GraphCodeBERT for Code Similarity Tasks
Assessing the degree of similarity of code fragments is crucial for ensuring software quality, but it remains challenging due to the need to capture the deeper semantic aspects of code. Traditional syntactic methods ofte…
Clone DetectionThe Struggles of LLMs in Cross-lingual Code Clone Detection
With the involvement of multiple programming languages in modern software development, cross-lingual code clone detection has gained traction within the software engineering community. Numerous studies have explored this…
Clone DetectionEliminating Backdoors in Neural Code Models for Secure Code Understanding
Neural code models (NCMs) have been widely used to address various code understanding tasks, such as defect detection. However, numerous recent studies reveal that such models are vulnerable to backdoor attacks. Backdoor…
Autonomous Drivingbackdoor defenseClone DetectionDefect DetectionDeepCodeProbe: Towards Understanding What Models Trained on Code Learn
Machine learning models trained on code and related artifacts offer valuable support for software maintenance but suffer from interpretability issues due to their complex internal variables. These concerns are particular…
Clone DetectionCode SummarizationComment GenerationDecision Making+1Assessing the Code Clone Detection Capability of Large Language Models
This study aims to assess the performance of two advanced Large Language Models (LLMs), GPT-3.5 and GPT-4, in the task of code clone detection. The evaluation involves testing the models on a variety of code pairs of dif…
Clone DetectionCode GenerationSimClone: Detecting Tabular Data Clones using Value Similarity
Data clones are defined as multiple copies of the same data among datasets. Presence of data clones between datasets can cause issues such as difficulties in managing data assets and data license violations when using da…
Clone DetectionToward Exploring the Code Understanding Capabilities of Pre-trained Code Generation Models
Recently, large code generation models trained in a self-supervised manner on extensive unlabeled programming language data have achieved remarkable success. While these models acquire vast amounts of code knowledge, the…
Clone DetectionCode GenerationCode SearchContrastive Learning+1Advanced Detection of Source Code Clones via an Ensemble of Unsupervised Similarity Measures
The capability of accurately determining code similarity is crucial in many tasks related to software development. For example, it might be essential to identify code duplicates for performing software maintenance. This …
Clone DetectionCode SearchEnsemble LearningGenCode: A Generic Data Augmentation Framework for Boosting Deep Learning-Based Code Understanding
Pre-trained code models lead the era of code intelligence with multiple models have been designed with impressive performance. However, one important problem, data augmentation for code data that automatically helps deve…
Clone DetectionData AugmentationTrained Without My Consent: Detecting Code Inclusion In Language Models Trained on Code
Code auditing ensures that the developed code adheres to standards, regulations, and copyright protection by verifying that it does not contain code from protected sources. The recent advent of Large Language Models (LLM…
Clone DetectionInvestigating the Efficacy of Large Language Models for Code Clone Detection
Large Language Models (LLMs) have demonstrated remarkable success in various natural language processing and software engineering tasks, such as code generation. The LLMs are mainly utilized in the prompt-based zero/few-…
Clone DetectionCode Comment GenerationCode GenerationComment Generation