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Exponential Automatic Amortized Resource Analysis

机译:指数自动摊销资源分析

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Automatic amortized resource analysis (AARA) is a type-based technique for inferring concrete (non-asymptotic) bounds on a program's resource usage. Existing work on AARA has focused on bounds that are polynomial in the sizes of the inputs. This paper presents and extension of AARA to exponential bounds that preserves the benefits of the technique, such as compositionality and efficient type inference based on linear constraint solving. A key idea is the use of the Stirling numbers of the second kind as the basis of potential functions, which play the same role as the binomial coefficients in polynomial AARA. To formalize the similarities with the existing analyses, the paper presents a general methodology for AARA that is instantiated to the polynomial version, the exponential version, and a combined system with potential functions that are formed by products of Stirling numbers and binomial coefficients. The soundness of exponential AARA is proved with respect to an operational cost semantics and the analysis of representative example programs demonstrates the effectiveness of the new analysis.
机译:自动摊销资源分析(AARA)是一种基于类型的技术,可以推断程序资源使用的具体(非渐近)范围。有关AARA的现有工作集中在输入大小为多项式的边界上。本文介绍了AARA并将其扩展到指数范围,从而保留了该技术的优势,例如基于线性约束求解的组合性和有效类型推断。一个关键思想是使用第二种斯特林数作为势函数的基础,这些函数与多项式AARA中的二项式系数具有相同的作用。为了形式化与现有分析的相似性,本文提出了一种用于AARA的通用方法,该方法实例化为多项式,指数型以及具有潜在功能的组合系统,该系统由斯特林数和二项式系数的乘积形成。相对于运营成本语义,证明了指数AARA的正确性,对代表性示例程序的分析证明了新分析的有效性。

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