Non-enumerative path delay fault diagnosis [logic testing]

Padmanaban, Saravanan; Tragoudas, Spyros

doi:10.1109/date.2003.1253627

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…The existing methods can be classified into two categories: (1) Fault-model-based diagnosis [1][2][3][4][5], and (2) Reasoning-based diagnosis [6][7][8]. For fault-model-based diagnosis, the cause of a timing failure is modeled as a fault such as a transition fault or a path-delay fault.…”

Section: Introductionmentioning

confidence: 99%

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Timing-reasoning-based delay fault diagnosis

Yang

Cheng

2006

Proceedings of the Design Automation &Amp; Test in Europe Conference

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In this paper, we propose a timing-reasoning algorithm to improve the resolution of delay fault diagnosis. In contrast to previous approaches which identify candidates by utilizing only logic conditions, we propose a timing-simulationbased method to perform the candidate reasoning. Based on the circuit timing information, we identify invalid candidates which cannot maintain the consistency of failure behaviors. By eliminating those invalid candidates, the diagnosis resolution can be improved. We then analyze the problem of circuit timing uncertainty caused by the delay variation and the simulation model. We calculate a metric, named invalid-probability, for each candidate. Then we propose a candidate-ranking heuristic which is robust with respect to such sources of timing uncertainty. By ranking the candidates based on their invalid-probability, we can improve the candidate first-hit-rate of the traditional critical path tracing (CPT) technique. To demonstrate the efficiency of the proposed method, we have developed a timing diagnosis framework which can simulate the real diagnosis process to evaluate and compare different algorithms.

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Section: Introductionmentioning

confidence: 99%

“…Moreover, the applied timing model is fixed, which may affect the result in the presence of delay variations. The methods proposed in [3][4][5] apply the pathdelay-fault model. In [3], the authors propose an efficient algorithm to identify the sensitized paths based on ZBDD.…”

Section: Introductionmentioning

confidence: 99%