Arty Starr, Keith Mann, Margaret‐Anne Storey · 2026 · arXiv (Cornell University)
DOI: 10.48550/arxiv.2610.24935 · cited by 0 works (OpenAlex) · open-access PDF
该论文介绍了开发者动力数据理论,这有助于我们看到在移动中开发软件的活动和进展所带来的熟练工艺。我们将开发者动力定义为开发者的进展和向前移动的经验,以达到任务的目标。我们的理论分散了流动状态,动力和动机的相关构造,因此我们可以更清楚地看到它们之间的关系,以及它们如何相互交织以支持进展。为了使进展,开发人员在记忆中建立工作背景,沉浸在认知谜题中,并通过在不确定地形中运动获得清晰度。理论为研究人员提供了一个丰富的体验镜头来调查开发者的认知经验如何在新兴AI流动中移动。 建立在预先定义的理论工作上,我们对12位专业人士的理论上采用的样本进行深入采访,开发了
Machine translation (Meta M2M100); the English original follows.
This paper introduces a Theory of Developer Momentum that helps us see the activity of developing software in motion and the skilled craft through which progress unfolds. We define Developer Momentum as the developer's experience of progress and forward motion toward the goal of a task. Our theory disentangles the related constructs of flow state, momentum, and motivation, so we can more clearly see the relationships between them and how they interweave to support progress. In order to make progress, developers build up working context in memory, become immersed in a cognitive puzzle, and gain clarity through motion in uncertain terrain. The theory provides researchers with a rich experiential lens to investigate how developers' cognitive experiences are shifting in emerging AI workflows. Building on prior grounded theory work, we conducted in-depth interviews with a theoretically sampled subset of 12 professional developers, and eight feedback interviews to evaluate resonance and investigate how the theory translates to agentic AI workflows. We followed a Constructivist Grounded Theory approach to construct a theory grounded in empirical data. Our theory contributes a novel paradigm for seeing the motion of developing software at multiple scales and resolutions, seeing the living capacities that support this motion, and expanding what becomes available for improvement, skilled judgment, and craft.
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Topics: Grounded theory, Craft, Motion (physics), CLARITY, Experiential learning, Context (archaeology)
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