IODINE: a tool to automatically infer dynamic invariants for hardware designs

  • Authors:
  • Sudheendra Hangal;Naveen Chandra;Sridhar Narayanan;Sandeep Chakravorty

  • Affiliations:
  • Sun Microsystems, Bangalore, India;Sun Microsystems, Bangalore, India;P. A. Semi Inc, Santa Clara, CA;Sun Microsystems, Bangalore, India

  • Venue:
  • Proceedings of the 42nd annual Design Automation Conference
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

We describe IODINE, a tool to automatically extract likely design properties using dynamic analysis. A practical bottleneck in the formal verication of hardware designs is the need to manually specify design-specic properties. IODINE presents a way to automatically extract properties such as state machine protocols, request-acknowledge pairs, and mutual exclusion between signals from design simulations. We show that dynamic invariant detection for hardware designs can infer relevant and accurate properties.