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AI也能写代码,“让软件开发工作变得更高效”
Guan Cha Zhe Wang· 2025-07-29 03:46
Core Viewpoint - The rapid advancement of artificial intelligence (AI) technology is significantly aiding various fields, including computer programming, with tools like Cursor, GitHub Copilot, and domestic AI programming models enhancing developer efficiency [1][3]. Group 1: AI Programming Tools - Anysphere's Cursor, GitHub Copilot developed by GitHub and OpenAI, and other AI programming tools are widely used for code dialogue, completion, and editing [1]. - Companies like SenseTime, Alibaba, and iFlytek showcased multiple AI programming tools at the 2025 World Artificial Intelligence Conference, aimed at assisting developers in coding tasks [1]. - iFlyCode by iFlytek is based on a large model and offers features such as intelligent Q&A, code completion, optimization, and test case generation [1]. - Alibaba Cloud's Tongyi Lingma can autonomously make decisions and utilize tools to complete coding tasks end-to-end based on developer requirements [1]. Group 2: Software Development Assistance - SenseTime's Code Xiaohuanxiong supports AI model-based code dialogue, completion, editing, and covers various software development stages, catering to both individual developers and enterprise projects [3]. - The tool aims to enhance efficiency across different roles in software development, streamline communication, and organize existing code to avoid redundancy [3]. Group 3: Developer Experience and AI Impact - A study by METR indicated that AI-assisted programming might slow down experienced developers, who initially expected a 24% reduction in task completion time but experienced a 19% increase instead [5]. - The slowdown is attributed to the time spent checking and correcting AI suggestions, although AI tools can still benefit junior developers and those unfamiliar with certain codebases [5]. - Different levels of developers experience varying benefits from AI tools, with junior developers valuing code completion features more than senior developers, who often use AI as a system or search engine [5][6]. Group 4: Natural Language Programming - The emergence of natural language programming allows developers to use simple text descriptions to accomplish tasks, making programming more intuitive [6]. - However, the complexity and ambiguity of human language pose challenges in developing this technology [6][7]. - Future programming languages may evolve to combine natural language elements with standard syntax to lower barriers for developers while ensuring programming effectiveness [7].