Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study

Research article (2023 IEEE/ACM 20th International Conference on Mining Software Repositories (MSR), 2023) · cited 10× · AI/ML
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Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study

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Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study. Retrieved May 24, 2026, from https://4ort.xyz/entity/enriching-source-code-with-contextual-data-for-code-completion-models-an-empirical-study
MLA “Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/enriching-source-code-with-contextual-data-for-code-completion-models-an-empirical-study.
BibTeX @misc{4ortxyz_enriching-source-code-with-contextual-data-for-code-completion-models-an-empirical-study_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study}}, year = {2026}, url = {https://4ort.xyz/entity/enriching-source-code-with-contextual-data-for-code-completion-models-an-empirical-study}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study — https://4ort.xyz/entity/enriching-source-code-with-contextual-data-for-code-completion-models-an-empirical-study (retrieved 2026-05-24)

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