Fully Abstract Semantics for Practical Languages

在构建程序优化的数学框架时，需要完全抽象的编程语言的语义定义。特别是，需要捕获实际语言中程序短语的可观察行为。今天，指称语言规范经常对行为难以区分的程序短语进行人为区分。在这个项目中采用了一种新的方法，该方法基于对模型中误差值和误差传播的现实处理。在存在错误元素的情况下，序列函数在按点排序的情况下形成一个普通的Scott-域，并且可以表示为决策树。这有助于隐式描述错误是如何传播的。这种方法将被用来定义诸如FORTRAN、PASCAL、C、ML和SCHEMA等实用语言。

Semantic definitions for programming languages which are fully abstract are needed in the construction of a mathematical framework for program optimization. In particular, the observable behavior of program phrases in practical languages needs to be captured. Today, denotational language specifications often make artificial distinctions between program phrases with indistinguishable behavior. A new approach based upon a realistic treatment of error values and error propagation in models is utilized in this project. Sequential functions form an ordinary Scott-domain under pointwise ordering in the presence of error elements and can be represented as decision trees. This helps to implicitly describe how errors are propagated. This approach will be used to define practical languages such as FORTRAN, Pascal, C, ML, and Scheme.