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‎paper-abstracts.json‎

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‎papers.html‎

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‎publications-metadata/bavishi2019autopandas.json‎

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[["nguyen2016mapping", "Mapping API Elements for Code Migration with Vector Representations"], ["nguyen2014statistical", "Statistical Learning Approach for Mining API Usage Mappings for Code Migration"], ["gu2017deepam", "DeepAM: Migrate APIs with Multi-modal Sequence to Sequence Learning"], ["wong2021leveraging", "Leveraging Language to Learn Program Abstractions and Search Heuristics"]]
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[["nguyen2016mapping", "Mapping API Elements for Code Migration with Vector Representations"], ["nguyen2014statistical", "Statistical Learning Approach for Mining API Usage Mappings for Code Migration"], ["chen2019mining", "Mining Likely Analogical APIs across Third-Party Libraries via Large-Scale Unsupervised API Semantics Embedding"], ["wong2021leveraging", "Leveraging Language to Learn Program Abstractions and Search Heuristics"]]

‎publications-metadata/briem2020offside.json‎

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[["pradel2017deep", "Deep Learning to Find Bugs"], ["li2019improving", "Improving Bug Detection via Context-Based Code Representation Learning and Attention-Based Neural Networks"], ["liu2018neural", "Neural-Machine-Translation-Based Commit Message Generation: How Far Are We?"], ["patra2021semantic", "A Semantic Bug Seeding: A Learning-Based Approach for Creating Realistic Bugs"]]
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[["pradel2017deep", "Deep Learning to Find Bugs"], ["li2019improving", "Improving Bug Detection via Context-Based Code Representation Learning and Attention-Based Neural Networks"], ["liu2018neural", "Neural-Machine-Translation-Based Commit Message Generation: How Far Are We?"], ["saini2018oreo", "Oreo: detection of clones in the twilight zone"]]

‎publications-metadata/bui2021infercode.json‎

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[["deze2022bridging", "Bridging Pre-trained Models and Downstream Tasks for Source Code Understanding"], ["deze2021mulcode", "MulCode: A Multi-task Learning Approach for Source Code Understanding"], ["hussain2019deep", "Deep Transfer Learning for Source Code Modeling"], ["siow2022learning", "Learning Program Semantics with Code Representations: An Empirical Study"]]
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[["deze2022bridging", "Bridging Pre-trained Models and Downstream Tasks for Source Code Understanding"], ["niu2022spt-code", "SPT-Code: Sequence-to-Sequence Pre-Training for Learning Source Code Representations"], ["deze2021mulcode", "MulCode: A Multi-task Learning Approach for Source Code Understanding"], ["hussain2019deep", "Deep Transfer Learning for Source Code Modeling"]]

‎publications-metadata/chen2019mining.json‎

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[["nguyen2017exploring", "Exploring API Embedding for API Usages and Applications"], ["gu2017deepam", "DeepAM: Migrate APIs with Multi-modal Sequence to Sequence Learning"], ["nguyen2016mapping", "Mapping API Elements for Code Migration with Vector Representations"], ["nguyen2014statistical", "Statistical Learning Approach for Mining API Usage Mappings for Code Migration"]]
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[["nguyen2017exploring", "Exploring API Embedding for API Usages and Applications"], ["nguyen2016mapping", "Mapping API Elements for Code Migration with Vector Representations"], ["nguyen2014statistical", "Statistical Learning Approach for Mining API Usage Mappings for Code Migration"], ["gu2017deepam", "DeepAM: Migrate APIs with Multi-modal Sequence to Sequence Learning"]]

‎publications-metadata/clement2020pymt5.json‎

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[["barone2017parallel", "A parallel corpus of Python functions and documentation strings for automated code documentation and code generation"], ["aggarwal2015using", "Using Machine Translation for Converting Python 2 to Python 3 Code"], ["gros2020code", "Code to Comment \"Translation\": Data, Metrics, Baselining & Evaluation"], ["loyola2018content", "Content Aware Source Code Change Description Generation"]]
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[["barone2017parallel", "A parallel corpus of Python functions and documentation strings for automated code documentation and code generation"], ["aggarwal2015using", "Using Machine Translation for Converting Python 2 to Python 3 Code"], ["gros2020code", "Code to Comment \"Translation\": Data, Metrics, Baselining & Evaluation"], ["roziere2021leveraging", "Leveraging Automated Unit Tests for Unsupervised Code Translation"]]

‎publications-metadata/clement2021distilling.json‎

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[["husain2019codesearchnet", "CodeSearchNet Challenge: Evaluating the State of Semantic Code Search"], ["li2019neural", "Neural Code Search Evaluation Dataset"], ["nadeem2022codedsi", "CodeDSI: Differentiable Code Search"], ["chirkova2020empirical", "Empirical Study of Transformers for Source Code"]]
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[["husain2019codesearchnet", "CodeSearchNet Challenge: Evaluating the State of Semantic Code Search"], ["li2019neural", "Neural Code Search Evaluation Dataset"], ["nadeem2022codedsi", "CodeDSI: Differentiable Code Search"], ["derezendemartins2020concra.md", "CoNCRA: A Convolutional Neural Network Code Retrieval Approach"]]

‎publications-metadata/doderlein2022piloting.json‎

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[["chen2022codet", "CodeT: Code Generation with Generated Tests"], ["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"], ["barke2022grounded", "Grounded Copilot: How Programmers Interact with Code-Generating Models"], ["xu2022systematic", "A Systematic Evaluation of Large Language Models of Code"]]
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[["chen2022codet", "CodeT: Code Generation with Generated Tests"], ["barke2022grounded", "Grounded Copilot: How Programmers Interact with Code-Generating Models"], ["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"], ["xu2022systematic", "A Systematic Evaluation of Large Language Models of Code"]]

‎publications-metadata/fowkes2016parameter.json‎

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[["nguyen2017exploring", "Exploring API Embedding for API Usages and Applications"], ["nguyen2016learning", "Learning API Usages from Bytecode: A Statistical Approach"], ["gu2017deepam", "DeepAM: Migrate APIs with Multi-modal Sequence to Sequence Learning"], ["chen2019mining", "Mining Likely Analogical APIs across Third-Party Libraries via Large-Scale Unsupervised API Semantics Embedding"]]
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[["nguyen2017exploring", "Exploring API Embedding for API Usages and Applications"], ["nguyen2016learning", "Learning API Usages from Bytecode: A Statistical Approach"], ["chen2019mining", "Mining Likely Analogical APIs across Third-Party Libraries via Large-Scale Unsupervised API Semantics Embedding"], ["nguyen2016mapping", "Mapping API Elements for Code Migration with Vector Representations"]]

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