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
이 논문은 개발자 동향의 데이터 이론을 소개합니다.이 논문은 진행 중인 소프트웨어 개발 활동과 진보를 촉진시키는 숙련 된 기관을 볼 수 있도록 도와줍니다. 우리는 개발자 동향을 작업 목표를 향한 진전과 앞으로 이동의 개발자의 경험으로 정의합니다. 우리의 이론은 흐름 상태, 동향 및 동기 부여의 관련 구조를 분리합니다. 그래서 우리는 진전을 지원하기 위해 그들 사이의 관계를 더 명확하게 볼 수 있습니다. 진전을 구축하기 위해 개발자들은 기억 속에서 일하는 맥락을 구축하고, 인지적 퍼즐에 몰두하고, 불확실한 지형에서 움직임을 통해 명확성을 얻습니다. 이론은 연구자들에게 풍부한 경험 렌즈를 제공합니다. 개발자의 인지적 경험이 어떻게
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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