一句话：提出 PRIME 工具，计算并可视化过程指标的纵向趋势，弥补快照指标不足。
软件指标能反映开发过程与产品信息，并支持团队管理、依赖选择等决策；但现有工具多只度量项目某一时刻的快照，较少支持工程师理解指标随时间演变的趋势，即关注过程而非仅产品的纵向指标。为此，作者提出 PRIME（PRocess MEtrics），一个计算与可视化过程指标的工具，目前支持生产力、问题密度、问题腐化/积压和巴士因子等指标。论文通过工具演示和案例说明纵向数据的价值，并给出后续研究议程。摘要未报告大规模实证评估或用户研究，主要贡献是工具与研究方向。
Software metrics capture information about software development processes and products. These metrics support decision-making, e.g., in team management or dependency selection. However, existing metrics tools measure only a snapshot of a software project. Little attention has been given to enabling engineers to reason about metric trends over time—longitudinal metrics that give insight about process, not just product. In this work, we present PRIME (PRocess MEtrics), a tool to compute and visualize process metrics. The currently-supported metrics include productivity, issue density, issue spoilage, and bus factor. We illustrate the value of longitudinal data and conclude with a research agenda. The tool’s demo video can be watched at https://bit.ly/ase2022-prime. Source code can be found at https://github.com/SoftwareSystemsLaboratory/prime.
@inproceedings{paperbot7263,
title = {Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics},
author = {Nicholas M. Synovic and Matt Hyatt and Rohan Sethi and Sohini Thota and Shilpika and Allan J. Miller and Wenxin Jiang and Emmanuel S. Amobi and Austin Pinderski and Konstantin Läufer and Nicholas J. Hayward and Neil Klingensmith and James C. Davis and George K. Thiruvathukal},
booktitle = {ASE},
year = {2022},
doi = {10.1145/3551349.3559517}
}