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| Main Author: | |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.08648 |
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| _version_ | 1866917951756566528 |
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| author | Peiris, H. R Navod Thisura |
| author_facet | Peiris, H. R Navod Thisura |
| contents | Code suggestions have become an integral part of IDEs and developers use code suggestions generated by IDEs all the time. These code suggestions are mostly for calling a method of an object or for using a function of a library and not for possible next line of the code. GPT based models are too slow or resource intensive for real-time code suggestions in local environments. As a solution to this GraphSense was introduced which provide code suggestions with minimum amount of resource usage in real-time. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_08648 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | GraphSense: Graph Embedding Based Code Suggestion Framework Peiris, H. R Navod Thisura Software Engineering 68N01 D.2.13 Code suggestions have become an integral part of IDEs and developers use code suggestions generated by IDEs all the time. These code suggestions are mostly for calling a method of an object or for using a function of a library and not for possible next line of the code. GPT based models are too slow or resource intensive for real-time code suggestions in local environments. As a solution to this GraphSense was introduced which provide code suggestions with minimum amount of resource usage in real-time. |
| title | GraphSense: Graph Embedding Based Code Suggestion Framework |
| topic | Software Engineering 68N01 D.2.13 |
| url | https://arxiv.org/abs/2503.08648 |