Journal Article10.1145/502175.502186
An exact solution to the minimum size test pattern problem
TL;DR: In this article, the problem of test pattern generation for single stuck-at faults in combinational circuits, under the additional constraint that the number of specified primary input assignments is minimized, is addressed.
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Abstract: This article addresses the problem of test pattern generation for single stuck-at faults in combinational circuits, under the additional constraint that the number of specified primary input assignments is minimized. This problem has different applications in testing, including the identification of "don't care" conditions to be used in the synthesis of Built-In Self-Test (BIST) logic. The proposed solution is based on an integer linear programming (ILP) formulation which builds on an existing Propositional Satisfiability (SAT) model for test pattern generation. The resulting ILP formulation is linear on the size of the original SAT model for test generation, which is linear on the size of the circuit. Nevertheless, the resulting ILP instances represent complex optimization problems, that require dedicated ILP algorithms. Preliminary results on benchmark circuits validate the practical applicability of the test pattern minimization model and associated ILP algorithm.
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Citations
Exact and Approximate Algorithms for the Optimization of Area and Delay in Multiple Constant Multiplications
TL;DR: This paper proposes an exact common subexpression elimination algorithm for the optimum sharing of partial terms in multiple constant multiplications (MCMs) and describes how this algorithm can be modified to target the minimum area solution under a user-specified delay constraint.
Algorithms for solving Boolean satisfiability in combinational circuits
L. Guerra e Silva,Luis Miguel Silveira,Joao Marques-Silva +2 more
- 01 Jan 1999
TL;DR: This paper describes how Boolean satisfiability algorithms can take circuit structure into account when solving instances derived from combinational circuits and provides clear evidence that computed solutions can have significantly less specified variable assignments than those obtained with common SAT algorithms.
On the size and generation of minimal N-detection tests
K.R. Kantipudi,Vishwani D. Agrawal +1 more
- 03 Jan 2006
TL;DR: An integer linear programming (ILP) algorithm for optimally minimizing a given test set for any given N is given; in general, the value of N can be separately specified for each fault.
On Optimization-Based ATPG and Its Application for Highly Compacted Test Sets
TL;DR: Experimental results show that the proposed SAT-based ATPG, based on a novel multiple-target test generation formulation using optimization techniques, is able to produce highly compacted test sets with high fault coverage for stuck-at as well as transition faults.
24
Provably optimal test cube generation using quantified boolean formula solving
Matthias Sauer,Sven Reimer,Ilia Polian,Tobias Schubert,Bernd Becker +4 more
- 29 Apr 2013
TL;DR: This work presents for the first time a framework that yields provably optimal test cubes by using the theory of quantified Boolean formulas (QBF) and demonstrates the quality gain of the proposed method.
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