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P2 ZION: System Exploration With Class Contours

ZION:基于类轮廓的系统探索
FSE Proceedings of the 34th ACM International Conference on the Foundations of Software Engineering2026匹配度 2/10 · 该论文属于软件可视化与程序理解工具,通过建筑轮廓隐喻帮助识别类角色和代码模式,与用户关注的静态分析、LLM/Agent、浮点程序分析及贝叶斯程序分析均无直接交叉。引用 0 inbox
Mattia Giannaccari, Marco Raglianti, Michele Lanza
crossref: 2026-09-12dblp: 2026-09-12

AI 速览

一句话:提出将类可视化为二维建筑轮廓的工具 ZION,帮助快速识别类角色与代码模式。

理解面向对象系统中类的结构与行为、识别其角色对软件维护与演化至关重要,但直接阅读源码难以快速理解,IDE 中类只是长文本流,outline 也仅是权宜之计。ZION 提出将类可视化为二维建筑结构,定义 Class Contours:把类组件(属性、方法、实例侧与类侧代码)编码为可定制的建筑特征(门、窗等),从而生成针对性的可视化。通过设计说明、功能展示与示例,作者表明涌现的视觉模式与交互式导航有助于识别类角色、常见原型与应用逻辑热点,提升对复杂软件系统的理解。

问题
面向对象系统中类在 IDE 里以长文本流呈现,开发者难以快速理解其结构、识别类的角色与代码模式。
方法
提出 ZION 工具,将类表示为二维建筑轮廓(Class Contours),把属性、方法、实例侧与类侧代码等组件映射为可定制的建筑特征,以生成可交互的可视化。
评估
通过工具设计介绍、功能展示和示例演示,说明涌现的视觉模式与交互式导航如何帮助理解类角色与复杂软件系统;未报告用户研究或量化评估。
原文摘要(Abstract)

Understanding the structure and behavior of classes and their roles in a software system is essential for maintaining and evolving object-oriented software. Reading source code provides limited support for quick comprehension or pattern identification. A class as a long stream of text in the IDE fails to communicate crucial information about its different components (e.g., attributes, methods, instance vs. class side code), while IDE outlines are just a band-aid solution. We present ZION, our tool to visualize the source code by representing classes as 2D architectural structures. ZION defines Class Contours by encoding class components (e.g., attributes, methods) into customizable building features (e.g., doors, windows). This allows tailored visualizations for identifying class roles and patterns, common archetypes, and hotspots for application logic. We present ZION's design, its features, alongside examples to highlight how the emerging visual patterns and the interactive visualization navigation enhance understanding complex software systems.

链接与引用

DOI 原文 · PDF(开放获取) · DBLP

BibTeX
@inproceedings{GiannaccariRL26,
  title = {ZION: System Exploration With Class Contours},
  author = {Mattia Giannaccari and Marco Raglianti and Michele Lanza},
  booktitle = {FSE},
  year = {2026},
  doi = {10.1145/3803437.3806412}
}