Iterative [simulation-based genetics + deterministic techniques]= complete ATPG0

  • Authors:
  • Daniel G. Saab;Youssef G. Saab;Jacob A. Abraham

  • Affiliations:
  • Computer Science Department, University of Missouri, Columbia MO;-;Computer Engeeniring Research Center, University Of Texas at Austin, Austin, TX

  • Venue:
  • ICCAD '94 Proceedings of the 1994 IEEE/ACM international conference on Computer-aided design
  • Year:
  • 1994

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Abstract

Simulation-based test vector generators require much less computer time than deterministic ATPG but they generate longer test sequences and sometimes achieve lower fault coverage. This is due to the divergence in the search process. In this paper, we propose a correction technique for simulation-based ATPG. This technique is based on identifying the diverging state and on computing a fault cluster (faults close to each other). A set of candidate faults from the cluster is targeted with a deterministic ATPG and the resulting test sequence is used to restart the search process of the simulation-based technique. This above process is repeated until all faults are detected or proven to be redundant/untestable. The program implementing this approach has been used to generate tests with very high fault coverage, and runs about 10 times faster than traditional deterministic techniques with very good test quality in terms of test length and fault coverage.