标题： 带绑定器的变元结构的推广：一种用于结构代码比较的工具 显示英文标题

标题： Generalization of Variadic Structures with Binders: A Tool for Structural Code Comparison

摘要： 本文介绍了一种新颖的反统一算法，用于具有绑定器的变元结构的泛化，设计为一种灵活的结构代码比较工具。 通过结合处理变量绑定的名义技术以及对变元表达式（常见于抽象语法树和编程语言）的支持，该方法解决了关键挑战，例如过度强调绑定变量名称以及在代码片段中处理插入或删除的困难。 该算法区分原子和两种类型的变量（项变量和树状变量），以计算最佳泛化，最大程度地保留结构相似性，同时抽象系统差异。 它还提供详细信息以重建原始表达式并量化结构差异。 这些信息在代码克隆检测、重构和程序分析等任务中可能很有用。 通过引入可参数化的刚性函数，该技术提供了对相似性标准的细粒度控制，并减少了非确定性，使得能够灵活适应实际场景，在这些场景中应忽略微不足道的相似性。 尽管主要在代码相似性检测的背景下进行演示，但此框架广泛适用于任何需要精确比较变元和绑定器丰富的表示的场景。 显示英文摘要

摘要： This paper introduces a novel anti-unification algorithm for the generalization of variadic structures with binders, designed as a flexible tool for structural code comparison. By combining nominal techniques for handling variable binding with support for variadic expressions (common in abstract syntax trees and programming languages), the approach addresses key challenges such as overemphasis on bound variable names and difficulty handling insertions or deletions in code fragments. The algorithm distinguishes between atoms and two kinds of variables (term and hedge variables) to compute best generalizations that maximally preserve structural similarities while abstracting systematic differences. It also provides detailed information to reconstruct original expressions and quantify structural differences. This information can be useful in tasks like code clone detection, refactoring, and program analysis. By introducing a parametrizable rigidity function, the technique offers fine-grained control over similarity criteria and reduces nondeterminism, enabling flexible adaptation to practical scenarios where trivial similarities should be discounted. Although demonstrated primarily in the context of code similarity detection, this framework is broadly applicable wherever precise comparison of variadic and binder-rich representations is required.