Results 1 to 10 of about 23 (21)
CMCS: contrastive-metric learning via vector-level sampling and augmentation for code search [PDF]
Scientific ReportsCode search aims to search for code snippets from large codebase that are semantically related to natural query statements. Deep learning is a valuable method for solving code search tasks in which the quality of training data directly impacts the ...
Qihong Song, Haize Hu, Tebo Dai
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ExCS: accelerating code search with code expansion [PDF]
Scientific ReportsEfficiently searching and reusing code from expansive codebases is pivotal for enhancing developers’ productivity. In recent times, the emergence of deep learning-driven neural ranking models, characterized by their vast dimensions and intricate ...
Siwei Huang +3 more
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Employing Source Code Quality Analytics for Enriching Code Snippets Data
Data, 2023 The availability of code snippets in online repositories like GitHub has led to an uptick in code reuse, this way further supporting an open-source component-based development paradigm.
Thomas Karanikiotis +2 more
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Enhancing Semantic Code Search With Deep Graph Matching
IEEE Access, 2023 The job of discovering appropriate code snippets against a natural language query is an important task for software developers. Appropriate code retrieval increases software productivity and quality as well.
Nazia Bibi +5 more
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Journal of Sensors, Volume 2022, Issue 1, 2022., 2022 Developers will perform a lot of search behaviors when facing daily work tasks, searching for reusable code fragments, solutions to specific problems, algorithm designs, software documentation, and software tools from public repositories (including open source communities and forum blogs) or private repositories (internal software repositories, source ...
Aiqiao Xu, Yaxiang Fan
wiley +1 more source
[Retracted] An Intelligent Code Search Approach Using Hybrid Encoders
Wireless Communications and Mobile Computing, Volume 2021, Issue 1, 2021., 2021 The intelligent code search with natural language queries has become an important researching area in software engineering. In this paper, we propose a novel deep learning framework At‐CodeSM for source code search. The powerful code encoder in At‐CodeSM, which is implemented with an abstract syntax tree parsing algorithm (Tree‐LSTM) and token‐level ...
Yao Meng, Balakrishnan Nagaraj
wiley +1 more source
Learning Deep Semantic Model for Code Search using CodeSearchNet Corpus
, 2022 Semantic code search is the task of retrieving relevant code snippet given a natural language query. Different from typical information retrieval tasks, code search requires to bridge the semantic gap between the programming language and natural language, for better describing intrinsic concepts and semantics.
Wu, Chen, Yan, Ming
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CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
, 2019 Semantic code search is the task of retrieving relevant code given a natural language query. While related to other information retrieval tasks, it requires bridging the gap between the language used in code (often abbreviated and highly technical) and natural language more suitable to describe vague concepts and ideas. To enable evaluation of progress
Husain, Hamel +4 more
openaire +2 more sources
C2B: A Semantic Source Code Retrieval Model Using CodeT5 and Bi-LSTM
Applied SciencesTo enhance the software implementation process, developers frequently leverage preexisting code snippets by exploring an extensive codebase. Existing code search tools often rely on keyword- or syntactic-based methods and struggle to fully grasp the ...
Nazia Bibi +4 more
doaj +1 more source
Enhancing code search through query expansion: A fusion of LSTM with GloVe and BERT model (ECSQE)
Results in EngineeringIn software engineering efficient code retrieval is essential for developers to quickly access relevant code snippets from vast repositories. This study focuses on enhancing code search through query expansion, leveraging advanced word embedding ...
Nazia Bibi +4 more
doaj +1 more source