Embedding-based search in JetBrains IDEs
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866917576102117376 |
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| author | Abramov, Evgeny Palchikov, Nikolai |
| author_facet | Abramov, Evgeny Palchikov, Nikolai |
| contents | Most modern Integrated Development Environments (IDEs) and code editors have a feature to search across available functionality and items in an open project. In JetBrains IDEs, this feature is called Search Everywhere: it allows users to search for files, actions, classes, symbols, settings, and anything from VCS history from a single entry point. However, it works with the candidates obtained by algorithms that don't account for semantics, e.g., synonyms, complex word permutations, part of the speech modifications, and typos. In this work, we describe the machine learning approach we implemented to improve the discoverability of search items. We also share the obstacles encountered during this process and how we overcame them. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_14975 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Embedding-based search in JetBrains IDEs Abramov, Evgeny Palchikov, Nikolai Software Engineering Computation and Language Information Retrieval Machine Learning Most modern Integrated Development Environments (IDEs) and code editors have a feature to search across available functionality and items in an open project. In JetBrains IDEs, this feature is called Search Everywhere: it allows users to search for files, actions, classes, symbols, settings, and anything from VCS history from a single entry point. However, it works with the candidates obtained by algorithms that don't account for semantics, e.g., synonyms, complex word permutations, part of the speech modifications, and typos. In this work, we describe the machine learning approach we implemented to improve the discoverability of search items. We also share the obstacles encountered during this process and how we overcame them. |
| title | Embedding-based search in JetBrains IDEs |
| topic | Software Engineering Computation and Language Information Retrieval Machine Learning |
| url | https://arxiv.org/abs/2401.14975 |