Backward Analysis for Higher-Order Functions Using Inverse Images
Abstract
We propose a method for performing backward analysis on higher--order functional programming languages based on computing inverse images of functions over abstract domains. This method can be viewed as abstract interpretation done backward. Given an abstract semantics which supports forward analysis, we can transform it into an abstract semantics which performs backward analysis. We show that if the original abstract semantics is correct and computable, then the transformed version of the abstract semantics is also correct and computable. More specifically, given a forward abstract semantics of a higher--order functional language which is expressed in terms of Scott--closed powerdomains, we derive an backward abstraction semantics which is expressed in terms of Scott--open powerdomains. The derivation is shown to be correct and the relationships between forward analysis and backward analysis is established. We apply this method to the classic strictness analysis in functional languages...
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 01, 1991
- Accession Number
- AD1020198
Entities
People
- Benjamin M. Goldberg
- Tyng-ruey Chuang
Organizations
- Columbia University