一句话：提出 EQDAC，一种高效判定数据约束等价性的决策过程，用于检测金融科技系统中的冗余约束。
金融科技系统广泛使用数据约束来监控数据一致性和诊断异常数据操作，但开发过程中常冗余创建等价约束，拖慢系统并造成不必要告警。论文提出 EQDAC，用于判定数据约束等价性。方法上，先给出语义编码的符号表示，再引入两种轻量级分析分别用于反驳和证明等价，并证明其可在多项式时间内完成。作者在真实金融科技系统中对 30,801 条数据约束进行评估，EQDAC 在三小时内检测出 11,538 条等价约束；其等价搜索平均耗时 1.22 秒，支持提交时在线检查新约束。
Data constraints are widely used in FinTech systems for monitoring data consistency and diagnosing anomalous data manipulations. However, many equivalent data constraints are created redundantly during the development cycle, slowing down the FinTech systems and causing unnecessary alerts. We present EQDAC, an efficient decision procedure to determine the data constraint equivalence. We first propose the symbolic representation for semantic encoding and then introduce two light-weighted analyses to refute and prove the equivalence, respectively, which are proved to achieve in polynomial time. We evaluate EQDAC upon 30,801 data constraints in a FinTech system. It is shown that EQDAC detects 11,538 equivalent data constraints in three hours. It also supports efficient equivalence searching with an average time cost of 1.22 seconds, enabling the system to check new data constraints upon submission.
DOI 原文 · arXiv · PDF（开放获取） · DBLP
@inproceedings{WangFYPZ23,
title = {Verifying Data Constraint Equivalence in FinTech Systems},
author = {Chengpeng Wang and Gang Fan and Peisen Yao and Fuxiong Pan and Charles Zhang},
booktitle = {ICSE},
year = {2023},
doi = {10.1109/icse48619.2023.00117}
}