发表机构
University of Calgary; UFRPE; University of Hawai‘i at Mānoa（卡尔加里大学; 巴西联邦农村大学; 夏威夷大学马诺阿分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过探索性案例研究，揭示基于LLM的自动化在软件项目管理中影响规划、协调与治理，增加验证需求，并促使管理者更依赖判断与经验性学习。
AI 中文摘要
随着软件工程的发展，开发环境日益集成自动化支持，用于测试、分析和代码生成等任务，这要求项目管理协调人工工作和自动化工作流。在本文中，我们研究了软件项目经理如何感知与基于LLM的自动化相关的工作和学习需求的变化。受软件工程研究空白（该领域主要关注任务层面和以开发者为中心的LLM使用）的驱动，我们采用了探索性案例研究方法，以捕捉管理者对实践中自动化的看法。基于在一家大型、多项目软件组织中工作的软件项目经理的经验，我们的分析表明，基于LLM的自动化影响了规划、估算、协调、监控和治理活动，而非引入新的正式管理实践。参与者描述LLM已嵌入日常项目工作中，对生产力产生不均衡的影响，增加了审查和验证的需求，并降低了任务执行的可视性。这些效应导致对管理判断和协调的更大依赖。学习需求被认为是经验性和渐进式的，集中于理解LLM的能力和局限性、批判性评估生成的工件，以及指导团队内的负责任使用。这些发现为在基于LLM的自动化被整合到持续软件开发实践的环境中，软件项目管理工作的适应方式提供了经验证据。
英文摘要
As software engineering has evolved, development environments have increasingly integrated automated support for tasks such as testing, analysis, and code generation, requiring project management to coordinate both human work and automated workflows. In this paper, we investigate how software project managers perceive changes in their work and learning demands associated with LLM-based automation. Motivated by a gap in software engineering research, which has largely focused on task-level and developer-centered uses of LLMs, we adopted an exploratory case study approach to capture managerial perspectives on automation in practice. Based on the experience of software project managers working in a large, multi-project software organization, our analysis indicates that LLM-based automation influences planning, estimation, coordination, monitoring, and governance activities rather than introducing new formal management practices. Participants described LLMs as becoming embedded in everyday project work, producing uneven effects on productivity, increasing the need for review and validation, and reducing visibility into task execution. These effects contribute to greater reliance on managerial judgment and coordination. Learning demands were perceived as experiential and incremental, centered on understanding LLM capabilities and limitations, critically assessing generated artifacts, and guiding responsible use within teams. The findings provide empirical evidence on how software project management work is adapted in contexts where LLM-based automation is integrated into ongoing software development practice.
