Concise, type-safe, and efficient structural diffing

Sebastian Erdweg, Tamás Szabó, André Pacak
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引用次数: 3

Abstract

A structural diffing algorithm compares two pieces of tree-shaped data and computes their difference. Existing structural diffing algorithms either produce concise patches or ensure type safety, but never both. We present a new structural diffing algorithm called truediff that achieves both properties by treating subtrees as mutable, yet linearly typed resources. Mutation is required to derive concise patches that only mention changed nodes, but, in contrast to prior work, truediff guarantees all intermediate trees are well-typed. We formalize type safety, prove truediff has linear run time, and evaluate its performance and the conciseness of the derived patches empirically for real-world Python documents. While truediff ensures type safety, the size of its patches is on par with Gumtree, a popular untyped diffing implementation. Regardless, truediff outperforms Gumtree and a typed diffing implementation by an order of magnitude.
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简洁、类型安全、高效的结构划分
一种结构差分算法比较两段树状数据并计算它们的差值。现有的结构差分算法要么产生简洁的补丁,要么确保类型安全,但从来没有两者兼而有之。我们提出了一种新的结构差分算法truediff,它通过将子树视为可变的线性类型资源来实现这两个属性。需要进行突变才能获得只提及更改节点的简明补丁,但是,与之前的工作相反,truediff保证所有中间树都是类型良好的。我们将类型安全形式化,证明truediff具有线性运行时间,并根据实际Python文档经验评估其性能和派生补丁的简洁性。虽然truediff确保了类型安全,但它的补丁大小与Gumtree相当,后者是一种流行的无类型区分实现。无论如何,truediff的性能比Gumtree和一个类型区分实现高出一个数量级。
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