Abstracting Abstract Control (Extended)

TL;DR

This paper extends the abstracting abstract machines (AAM) approach to incorporate pushdown systems for more accurate static analysis of dynamic language features like control stack inspection and first-class continuations.

Contribution

It revises the AAM technique to target pushdown systems, enabling more precise analysis of dynamic language features using only abstract machines and memoization.

Findings

The approach applies to languages with closures and continuations.

It handles features like garbage collection and stack inspection.

Provides more accurate static analysis for dynamic languages.

Abstract

The strength of a dynamic language is also its weakness: run-time flexibility comes at the cost of compile-time predictability. Many of the hallmarks of dynamic languages such as closures, continuations, various forms of reflection, and a lack of static types make many programmers rejoice, while compiler writers, tool developers, and verification engineers lament. The dynamism of these features simply confounds statically reasoning about programs that use them. Consequently, static analyses for dynamic languages are few, far between, and seldom sound. The "abstracting abstract machines" (AAM) approach to constructing static analyses has recently been proposed as a method to ameliorate the difficulty of designing analyses for such language features. The approach, so called because it derives a function for the sound and computable approximation of program behavior starting from the abstract machine semantics of a language, provides a viable approach to dynamic language analysis since all that is required is a machine description of the interpreter. The original AAM recipe produces finite state abstractions, which cannot faithfully represent an interpreter's control stack. Recent advances have shown that higher-order programs can be approximated with pushdown systems. However, these automata theoretic models either break down on features that inspect or modify the control stack. In this paper, we tackle the problem of bringing pushdown flow analysis to the domain of dynamic language features. We revise the abstracting abstract machines technique to target the stronger computational model of pushdown systems. In place of automata theory, we use only abstract machines and memoization. As case studies, we show the technique applies to a language with closures, garbage collection, stack-inspection, and first-class composable continuations.