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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2401.16654 |
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| _version_ | 1866929228441714688 |
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| author | Saben, Clark Chandrasekar, Prashant |
| author_facet | Saben, Clark Chandrasekar, Prashant |
| contents | BLVRUN is a command line shell script designed to offer developers within the BLV community a succinct and insightful overview of traceback errors. Its primary function involves parsing errors and utilizing a refined large language model to generate informative error summaries. In terms of performance, our model rivals that of well-known models like ChatGPT or AI-chatbot plug-ins tailored for specific Integrated Development Environments (IDEs). Importantly, BLV users can seamlessly integrate this tool into their existing development workflows, eliminating the need for any modifications or adaptations to facilitate debugging tasks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_16654 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Enabling BLV Developers with LLM-driven Code Debugging Saben, Clark Chandrasekar, Prashant Human-Computer Interaction BLVRUN is a command line shell script designed to offer developers within the BLV community a succinct and insightful overview of traceback errors. Its primary function involves parsing errors and utilizing a refined large language model to generate informative error summaries. In terms of performance, our model rivals that of well-known models like ChatGPT or AI-chatbot plug-ins tailored for specific Integrated Development Environments (IDEs). Importantly, BLV users can seamlessly integrate this tool into their existing development workflows, eliminating the need for any modifications or adaptations to facilitate debugging tasks. |
| title | Enabling BLV Developers with LLM-driven Code Debugging |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2401.16654 |