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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2405.06164 |
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| _version_ | 1866911872811270144 |
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| author | Fumitake, Kawasaki Kishi, Shota Neve, James |
| author_facet | Fumitake, Kawasaki Kishi, Shota Neve, James |
| contents | The field of web and mobile software frameworks is relatively mature, with a large variety of tools in different languages that facilitate traditional app development where data in a relational database is displayed and modified. Our position is that many current frameworks became popular during single server deployment of MVC architecture apps, and do not facilitate modern aspects of app development such as cloud computing and the incorporation of emerging technologies such as AI. We present a novel framework which accomplishes these purposes, Skeet, which was recently released to general use, alongside an initial evaluation. Skeet provides an app structure that reflects current trends in architecture, and tool suites that allow developers with minimal knowledge of AI internals to easily incorporate such technologies into their apps and deploy them. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_06164 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Skeet: Towards a Lightweight Serverless Framework Supporting Modern AI-Driven App Development Fumitake, Kawasaki Kishi, Shota Neve, James Software Engineering Artificial Intelligence The field of web and mobile software frameworks is relatively mature, with a large variety of tools in different languages that facilitate traditional app development where data in a relational database is displayed and modified. Our position is that many current frameworks became popular during single server deployment of MVC architecture apps, and do not facilitate modern aspects of app development such as cloud computing and the incorporation of emerging technologies such as AI. We present a novel framework which accomplishes these purposes, Skeet, which was recently released to general use, alongside an initial evaluation. Skeet provides an app structure that reflects current trends in architecture, and tool suites that allow developers with minimal knowledge of AI internals to easily incorporate such technologies into their apps and deploy them. |
| title | Skeet: Towards a Lightweight Serverless Framework Supporting Modern AI-Driven App Development |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2405.06164 |