MultiMind: A Plug-in for the Implementation of Development Tasks Aided by AI Assistants
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
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2025
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| author | Donato, Benedetta Mariani, Leonardo Micucci, Daniela Riganelli, Oliviero Somaschini, Marco |
| author_facet | Donato, Benedetta Mariani, Leonardo Micucci, Daniela Riganelli, Oliviero Somaschini, Marco |
| contents | The integration of AI assistants into software development workflows is rapidly evolving, shifting from automation-assisted tasks to collaborative interactions between developers and AI. Large Language Models (LLMs) have demonstrated their effectiveness in several development activities, including code completion, test case generation, and documentation production. However, embedding AI-assisted tasks within Integrated Development Environments (IDEs) presents significant challenges. It requires designing mechanisms to invoke AI assistants at the appropriate time, coordinate interactions with multiple assistants, process the generated outputs, and present feedback in a way that seamlessly integrates with the development workflow. To address these issues, we introduce MultiMind, a Visual Studio Code plug-in that streamlines the creation of AI-assisted development tasks. MultiMind provides a modular and extensible framework, enabling developers to cost-effectively implement and experiment with new AI-powered interactions without the need for complex IDE customizations. MultiMind has been tested in two use cases: one for the automatic generation of code comments and the other about the definition of AI-powered chat. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_11014 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MultiMind: A Plug-in for the Implementation of Development Tasks Aided by AI Assistants Donato, Benedetta Mariani, Leonardo Micucci, Daniela Riganelli, Oliviero Somaschini, Marco Software Engineering The integration of AI assistants into software development workflows is rapidly evolving, shifting from automation-assisted tasks to collaborative interactions between developers and AI. Large Language Models (LLMs) have demonstrated their effectiveness in several development activities, including code completion, test case generation, and documentation production. However, embedding AI-assisted tasks within Integrated Development Environments (IDEs) presents significant challenges. It requires designing mechanisms to invoke AI assistants at the appropriate time, coordinate interactions with multiple assistants, process the generated outputs, and present feedback in a way that seamlessly integrates with the development workflow. To address these issues, we introduce MultiMind, a Visual Studio Code plug-in that streamlines the creation of AI-assisted development tasks. MultiMind provides a modular and extensible framework, enabling developers to cost-effectively implement and experiment with new AI-powered interactions without the need for complex IDE customizations. MultiMind has been tested in two use cases: one for the automatic generation of code comments and the other about the definition of AI-powered chat. |
| title | MultiMind: A Plug-in for the Implementation of Development Tasks Aided by AI Assistants |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2506.11014 |