用多维度指标量化开发者生产力，发现挫败感越强提交越频繁。
SpaceX: Exploring metrics with the SPACE model for developer productivity
- 基于代码库数据构建复合生产力评分模型，融合情感与协作网络。
- 发现负面情绪与提交频率显著正相关，反映挫败驱动的反复修复。
- 相比单纯统计提交量，网络拓扑分析更能揭示真实协作关系。
本研究通过大规模开源代码库挖掘，实证检验了单一维度生产力评估方法的局限性，提出并应用SPACE框架，结合广义线性混合模型（GLMM）与RoBERTa情感分类技术，构建多维度开发者生产力综合指标。分析显示，负面情绪状态与提交频率存在显著正相关，表明挫败感可能驱动迭代修复行为；同时，贡献者交互拓扑结构的分析在刻画协作动态方面优于传统以数量为基础的度量方式。最终，研究提出复合生产力得分（CPS），以应对开发者效能的异质性问题。
原文摘要 · Abstract (English)
This empirical investigation elucidates the limitations of deterministic, unidimensional productivity heuristics by operationalizing the SPACE framework through extensive repository mining. Utilizing a dataset derived from open-source repositories, the study employs rigorous statistical methodologies including Generalized Linear Mixed Models (GLMM) and RoBERTa-based sentiment classification to synthesize a holistic, multi-faceted productivity metric. Analytical results reveal a statistically significant positive correlation between negative affective states and commit frequency, implying a cycle of iterative remediation driven by frustration. Furthermore, the investigation has demonstrated that analyzing the topology of contributor interactions yields superior fidelity in mapping collaborative dynamics compared to traditional volume-based metrics. Ultimately, this research posits a Composite Productivity Score (CPS) to address the heterogeneity of developer efficacy.
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