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P2 Retrieving data constraint implementations using fine-grained code patterns

使用细粒度代码模式检索数据约束实现
ICSE Proceedings of the 44th International Conference on Software Engineering2022匹配度 3/10 · 该论文属于传统程序分析与静态分析,方向与用户的部分兴趣相关,但具体主题是业务规则与数据约束实现定位,未涉及 LLM/Agent、ML 系统静态分析、浮点程序分析或贝叶斯程序分析等核心交叉方向。引用 6 inbox
Juan Manuel Florez, Jonathan Perry, Shiyi Wei, Andrian Marcus
crossref: 2026-09-12dblp: 2026-09-12

AI 速览

一句话:提出用细粒度代码模式定位源代码中的数据约束实现,以支持业务规则变更。

业务规则是支持组织软件系统需求的重要部分,描述适用于组织的操作、定义和约束。在软件系统中,业务规则常被翻译成对数据值的要求或允许条件,即数据约束。业务规则频繁变化,因此对应数据约束也需修改。高效精确识别数据约束在源代码中的实现位置对完成此类修改至关重要。本文提出用细粒度代码模式检索数据约束实现。摘要未报告具体方法与评估结果。

问题
业务规则频繁变更时,如何高效、精确地在源代码中定位数据约束的实现位置。
方法
利用细粒度代码模式(fine-grained code patterns)来检索数据约束实现。
评估
摘要未提供具体评估细节;仅指出该能力对完成必要修改至关重要。
原文摘要(Abstract)

Business rules are an important part of the requirements of software systems that are meant to support an organization. These rules describe the operations, definitions, and constraints that apply to the organization. Within the software system, business rules are often translated into constraints on the values that are required or allowed for data, called data constraints. Business rules are subject to frequent changes, which in turn require changes to the corresponding data constraints in the software. The ability to efficiently and precisely identify where data constraints are implemented in the source code is essential for performing such necessary changes.

链接与引用

DOI 原文 · DBLP

BibTeX
@inproceedings{FlorezPWM22,
  title = {Retrieving data constraint implementations using fine-grained code patterns},
  author = {Juan Manuel Florez and Jonathan Perry and Shiyi Wei and Andrian Marcus},
  booktitle = {ICSE},
  year = {2022},
  doi = {10.1145/3510003.3510167}
}