In order to automatically infer the resource consumption of programs, analyzers track how data sizes change along program’s execution. Typically, analyzers measure the sizes of data by applying norms which are mappings from data to natural numbers that represent the sizes of the corresponding data. When norms are defined by taking type information into account, they are named typed-norms. This article presents a transformational approach to resource analysis with typed-norms that are inferred by a data-flow analysis. The analysis is based on a transformation of the program into an intermediate abstract program in which each variable is abstracted with respect to all considered norms which are valid for its type. We also present the data-flow analysis to automatically infer the required, useful, typed-norms from programs. Our analysis is formalized on a simple rule-based representation to which programs written in different programming paradigms (e.g., functional, logic, and imperative) can be automatically translated. Experimental results on standard benchmarks used by other type-based analyzers show that our approach is both efficient and accurate in practice.

中文翻译：

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具有类型规范推理的资源分析转换方法

为了自动推断程序的资源消耗，分析器跟踪如何数据大小随着程序的执行而改变。通常，分析器通过应用来测量数据的大小规范它们是从数据到表示相应数据大小的自然数的映射。当通过考虑类型信息来定义规范时，它们被命名为类型化规范. 本文介绍了一种使用数据流分析推断的类型规范的资源分析转换方法。该分析基于将程序转换为中间抽象程序其中每个变量都相对于对其类型有效的所有考虑的规范进行抽象。我们还展示了数据流分析，以自动从程序中推断出所需的、有用的、类型化的规范。我们的分析是基于简单的基于规则的表示形式化的，用不同的编程范式（例如，函数式、逻辑式和命令式）编写的程序可以自动翻译成该表示。其他基于类型的分析器使用的标准基准的实验结果表明，我们的方法在实践中既有效又准确。