Flow-Sensitive Control-Flow Analysis in Linear-Log Time

Abstract

The flexibility of dynamically typed languages such as JavaScript, Python, Ruby, and

Scheme comes at the cost of run-time type checks. Some of these checks can be eliminated

via control-flow analysis. However, traditional control-flow analysis (CFA) is not ideal for

this task as it ignores flow-sensitive information that can be gained from dynamic type

predicates, such as JavaScript's instanceof and Scheme's pair?, and from type-restricted

operators, such as Scheme's car. Yet, adding flow-sensitivity to a traditional CFA worsens

the already significant compile-time cost of traditional CFA. This makes it unsuitable for

use in just-in-time compilers.

In response, this dissertation presents a fast, flow-sensitive type-recovery algorithm based

on the linear-time, flow-insensitive sub-0CFA. The algorithm has been implemented as an

experimental optimization into Chez Scheme compiler, where it has proven to be effective,

justifying the elimination of about 60% of run-time type checks in a large set of bench-

marks. The algorithm processes on average over 100,000 lines of code per second and scales

well asymptotically, running in only O(n log n) time. This compile-time performance and

scalability is achieved through a novel combination of data structures and algorithms.