一句话：提出层次化LLM驱动并自验证的API指向规约生成方法，缓解第三方API复杂语义、语法与边界情况带来的静态分析困难。
静态分析是保障软件安全可靠的关键技术。当分析调用第三方API的客户端代码时，如何处理API源码成为核心问题。常见做法是使用API规约来近似API的关键行为，从而避免直接分析其实现。然而，现有API规约构造方法难以充分应对复杂语义、复杂语法以及边界情况等挑战。为此，本文提出SpecGuru：一种层次化、由大语言模型（LLM）驱动、带自验证机制的API points-to规约生成方法。该方法利用分层生成与自验证来提升规约质量，从而更好地支持调用第三方API的客户端代码静态分析。摘要未给出具体实验评估与量化结果。
Static analysis is a fundamental technique for ensuring software safety and reliability. However, when analyzing client code that invokes third-party APIs, proper handling of API source code becomes critical. A common approach is to utilize API specifications that approximate the essential behaviors of the API while avoiding direct analysis of the implementation. Existing methods for constructing API specifications often fail to adequately address challenges presented by complex semantics, syntax, and edge cases.
@inproceedings{paperbot11939,
title = {SpecGuru: Hierarchical LLM-Driven API Points-to Specification Generation with Self-Validation},
author = {Shuangxiang Kan and Yuekang Li and Xiao Cheng and Yulei Sui},
booktitle = {ICSE},
year = {2026},
doi = {10.1145/3744916.3773209}
}