一句话：提出通过自动条件独立性推理对因果发现算法进行运行时验证的方法。
因果发现算法在软件工程中广泛应用，其输出质量高度依赖条件独立性（CI）测试的性能，而 CI 测试在实践中往往不可靠，且大量 CI 测试会引发隐私问题。本文提出一种运行时验证方法，通过自动条件独立性推理来验证因果发现算法。摘要未提供具体评估结果，但标题表明该方法旨在提升因果发现算法的可靠性和隐私保护。
Causal discovery is a powerful technique for identifying causal relationships among variables in data. It has been widely used in various applications in software engineering. Causal discovery extensively involves conditional independence (CI) tests. Hence, its output quality highly depends on the performance of CI tests, which can often be unreliable in practice. Moreover, privacy concerns arise when excessive CI tests are performed.
DOI 原文 ·
@inproceedings{paperbot11245,
title = {Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning},
author = {Pingchuan Ma and Zhenlan Ji and Peisen Yao and Shuai Wang and Kui Ren},
booktitle = {ICSE},
year = {2024},
doi = {10.1145/3597503.3623348}
}