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P2 Moving towards objective measures of program comprehension

迈向程序理解的客观度量
FSE Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering2018匹配度 1/10 · 该论文属于经验软件工程/人机交互范畴,讨论程序理解研究中自评与总结等间接度量的偏差,主张采用客观度量;这与用户关注的静态分析、LLM/Agent 程序分析、浮点程序分析、贝叶斯程序分析等方向没有实质交集。引用 12 inbox
Sarah Fakhoury
crossref: 2026-09-12

AI 速览

一句话:指出程序理解研究依赖自评与总结等间接度量的偏差风险,主张转向客观度量。

程序理解研究长期依赖间接度量:让受试者自评理解程度,或让其总结部分制品,研究者再据此推断其理解水平。作者指出,这类间接度量存在若干潜在问题:一方面容易受到参与者偏差的影响,另一方面是隐式地依据多种因素去推断理解程度,从而使测量结果的可靠性存疑。基于此,本文主张转向客观度量(objective measures)来评估程序理解,以提升测量的有效性与可重复性。摘要属于问题诊断与研究议程的提出,未给出具体度量手段的细节,也未报告实验或评估结果。

问题
程序理解研究普遍依赖自我报告与制品总结等间接度量,这类度量易受参与者偏差影响,且以隐式方式推断理解水平,可靠性不足。
方法
提出研究议程,主张以客观度量替代间接度量来评估程序理解,从而更直接、更可靠地刻画理解水平。
评估
摘要未报告具体评估;该工作属于立场与议程性论述,以对现有间接度量问题的分析来支撑其方向性主张。
原文摘要(Abstract)

Traditionally, program comprehension research relies heavily on indirect measures of comprehension, where subjects report on their own comprehension levels or summarize part of an artifact so that researchers can instead deduce the level of comprehension. However, there are several potential issues that can result from using these indirect measures because they are prone to participant biases and implicitly deduce comprehension based on various factors.

链接与引用

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BibTeX
@inproceedings{paperbot4594,
  title = {Moving towards objective measures of program comprehension},
  author = {Sarah Fakhoury},
  booktitle = {FSE},
  year = {2018},
  doi = {10.1145/3236024.3275426}
}