Combined static and dynamic mutability analysis

  • Authors:

  • Shay Artzi;Adam Kiezun;David Glasser;Michael D. Ernst

  • Affiliations:

  • MIT, Cambridge, MA;MIT, Cambridge, MA;MIT, Cambridge, MA;MIT, Cambridge, MA

  • Venue:
  • Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

Knowing which method parameters may be mutated during a method's executionis useful for many software engineering tasks. We present an approach todiscovering parameter reference immutability, in which several lightweight, scalable analyses are combined in stages, with each stage refining the overall result. The resulting analysis is scalable and combines the strengths of its component analyses. As one of the component analyses, we present a novel, dynamic mutability analysis and show how its results can be improved by random input generation. Experimental results on programs of up to 185 kLOC show that, compared to previous approaches, our approach increases both scalability and overall accuracy