Virtual machine learning: Thinking like a computer architect
Michael Hind
CGO 2005
This paper describes an empirical comparison of the effectiveness of six context-insensitive pointer analysis algorithms that use varying degrees of flow-sensitivity. Four of the algorithms are flow-insensitive, one is flow-sensitive, and another is flow-insensitive, but uses precomputed flow-sensitive information. The effectiveness of each analysis is quantified in terms of compile-time efficiency and precision. Efficiency is reported by measuring CPU time and memory consumption of each analysis. Precision is reported by measuring the computed solutions at the program points where a pointer is dereferenced. The results of this paper will help implementors determine which pointer analysis is appropriate for their application.
Michael Hind
CGO 2005
Michael Hind, Dennis Wei, et al.
AIES 2019
Vijay Arya, Rachel K. E. Bellamy, et al.
IAAI 2022
Rachel Bellamy, Kuntal Dey, et al.
IEEE Software