On the complexity of flow-sensitive dataflow analyses

  • Authors:
  • Robert Muth;Saumya Debray

  • Affiliations:
  • Department of Computer Science, University of Arizona, Tucson, AZ;Department of Computer Science, University of Arizona, Tucson, AZ

  • Venue:
  • Proceedings of the 27th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
  • Year:
  • 2000

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper attempts to address the question of why certain dataflow analysis problems can be solved efficiently, but not others. We focus on flow-sensitive analyses, and give a simple and general result that shows that analyses that require the use of relational attributes for precision must be PSPACE-hard in general. We then show that if the language constructs are slightly strengthened to allow a computation to maintain a very limited summary of what happens along an execution path, inter-procedural analyses become EXPTIME-hard. We discuss applications of our results to a variety of analyses discussed in the literature. Our work elucidates the reasons behind the complexity results given by a number of authors, improves on a number of such complexity results, and exposes conceptual commonalities underlying such results that are not readily apparent otherwise.