Eecient Points-to Analysis for Whole-program Analysis

To function on programs written in languages such as C that make extensive use of pointers, automated software engineering tools require safe alias information. Existing alias-analysis techniques that are suuciently eecient for analysis on large software systems may provide alias information that is too imprecise for tools that use it: the impreci-sion of the alias information may (1) reduce the precision of the information provided by the tools and (2) increase the cost of the tools. This paper presents a ow-insensitive, context-sensitive points-to analysis algorithm that computes alias information that is almost as precise as that computed by Andersen's algorithm { the most precise ow-and context-insensitive algorithm { and almost as eecient as Steensgaard's algorithm { the most eecient ow-and context-insensitive algorithm. Our empirical studies show that our algorithm scales to large programs better than Andersen's algorithm and show that ow-insensitive alias analysis algorithms , such as our algorithm and Andersen's algorithm, can compute alias information that is close in precision to that computed by the more expensive ow-and context-sensitive alias analysis algorithms.