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.
. Flow-Sensitive Control-Flow Analysis in Linear-Log Time. Ph.D. thesis, Indiana University, 2011.
@phdthesis{adams2011cfa,
author = {Adams, Michael D.},
title = {Flow-Sensitive Control-Flow Analysis in Linear-Log Time},
school = {Indiana University},
year = {2011},
isbn = {978-1-267-07777-6},
}