一句话：呼吁先理解实践者对文档质量与任务所需信息的真实需求，以支撑自动文档推荐。
该文讨论软件文档在理论与实践中的落差：理论上良好文档是帮助利益相关者使用、理解、维护和演进系统的重要资产，但实践中文档常存在内容不足、不充分、过时和含糊等问题。为应对这些问题，研究者正探索构建先进的推荐系统，自动推荐对给定任务有用的高质量文档。论文指出，实现这一目标的关键第一步是理解实践者眼中文档质量的含义，以及特定任务究竟需要哪些信息。摘要主要提出研究问题与方向，强调需从实践者需求和任务上下文出发来界定文档质量与信息需求，从而为后续自动推荐技术奠定基础。
In theory, (good) documentation is an invaluable asset to any software project, as it helps stakeholders to use, understand, maintain, and evolve a system. In practice, however, documentation is generally affected by numerous shortcomings and issues, such as insufficient and inadequate content and obsolete, ambiguous information. To counter this, researchers are investigating the development of advanced recommender systems that automatically suggest high-quality documentation, useful for a given task. A crucial first step is to understand what quality means for practitioners and what information is actually needed for specific tasks.
DOI 原文 ·
@inproceedings{paperbot5560,
title = {Software documentation},
author = {Emad Aghajani and Csaba Nagy and Mario Linares-Vásquez and Laura Moreno and Gabriele Bavota and Michele Lanza and David C. Shepherd},
booktitle = {ICSE},
year = {2020},
doi = {10.1145/3377811.3380405}
}