In order to analyze a program that involves pointers, it is necessary to have (safe) information about what each pointer points to. There are many different approaches to computing points-to information. This paper addresses techniques for flow- and context-insensitive interprocedural analysis of stack-based storage.

The paper makes two contributions to work in this area:

• The first contribution is a set of experiments that explore the trade-offs between techniques previously defined by Lars Andersen and Bjarne Steensgaard. The former has a cubic worst-case running time, while the latter is essentially linear. However, the former may be much more precise than the latter. We have found that in practice, Andersen's algorithm is consistently more precise than Steensgaard's. For small programs, there is very little difference in the times required by the two approaches; however, for larger programs, Andersen's algorithm can be much slower than Steensgaard's.
• The second contribution is the definition of two new algorithms. The first algorithm can be ``tuned'' so that its worst-case time and space requirements, as well as its accuracy range from those of Steensgaard to those of Andersen. We have experimented with several versions of this algorithm; one version provided a significant increase in accuracy over Steensgaard's algorithm, while keeping the running time within a factor of two.

  The second algorithm uses the first as a subroutine. Its worst-case time and space requirements are a factor of log N (where N is the number of variables in the program) worse than those of Steensgaard's algorithm. In practice, it appears to run about ten times slower than Steensgaard's algorithm; however it is significantly more accurate than Steensgaard's algorithm, and significantly faster than Andersen's algorithm on large programs.