Benjamin Darnell, Hetarth Chopra, et al.
ICSE 2024
A large number of call graph construction algorithms for object-oriented and functional languages have been proposed, each embodying different tradeoffs between analysis cost and call graph precision. In this article we present a unifying framework for understanding call graph construction algorithms and an empirical comparison of a representative set of algorithms. We first present a general parameterized algorithm that encompasses many well-known and novel call graph construction algorithms. We have implemented this general algorithm in the Vortex compiler infrastructure, a mature, multilanguage, optimizing compiler. The Vortex implementation provides a "level playing field" for meaningful cross-algorithm performance comparisons. The costs and benefits of a number of call graph construction algorithms are empirically assessed by applying their Vortex implementation to a suite of sizeable (5,000 to 50,000 lines of code) Cecil and Java programs. For many of these applications, interprocedural analysis enabled substantial speed-ups over an already highly optimized baseline. Furthermore, a significant fraction of these speed-ups can be obtained through the use of a scalable, near-linear time call graph construction algorithm.
Benjamin Darnell, Hetarth Chopra, et al.
ICSE 2024
Claudia Misale, Olivier Tardieu, et al.
KubeCon EU 2025
Claudia Misale, David Grove
Cloud Native + Kubernetes AI Day 2025
Doug Lea, David F. Bacon, et al.
ACM SIGPLAN Notices