Test Pattern Generator for MV-Based QCA Combinational Circuit Targeting MMC Fault Models

Dhare, Vaishali; Mehta, Usha

doi:10.1080/03772063.2019.1674195

Cited by 3 publications

(6 citation statements)

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“…ATPG based on probability-based testability measures is proposed in [12]. It is proven in [9] that probability-based testability fails at reconvergent fanout. So, to overcome the limitations of probability-based testability measures, extended SCOAP testability measures for QCA are proposed in [9].…”

Section: B Testability Measuresmentioning

confidence: 99%

“…It is proven in [9] that probability-based testability fails at reconvergent fanout. So, to overcome the limitations of probability-based testability measures, extended SCOAP testability measures for QCA are proposed in [9]. In this work, the proposed ATPG is guided by testability measures proposed in [9].…”

Section: B Testability Measuresmentioning

confidence: 99%

“…So, to overcome the limitations of probability-based testability measures, extended SCOAP testability measures for QCA are proposed in [9]. In this work, the proposed ATPG is guided by testability measures proposed in [9]. C. QCA Circuit Synthesis Synthesized benchmark circuits for QCA technology are required to test the proposed ATPG.…”

Section: B Testability Measuresmentioning

confidence: 99%

“…In this paper, the advanced test generation algorithm is proposed to address the faults caused by single and multiple missing cell defects in combinational QCA circuits. Earlier, we have developed basic test generation algorithm [9,10] based on testability measures and testing properties [8].…”

Section: Introductionmentioning

confidence: 99%

“…Further, in [12], probability-based controllability measures are applied. In our previous work [9,10], it is shown that the probability-based approach fails in a circuit consisting of reconvergent fanouts. Therefore, Sandia Controllability Observability Analysis Program (SCOAP) [14] testability measures are extended for MVs and included in the proposed ATPG.…”

Section: Introductionmentioning

confidence: 99%

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Test Generation Algorithm for Quantum-dot Cellular Automata (QCA) Technology

Dhare

Mehta

2023

Preprint

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One of the alternatives to the current silicon technology, Complementary Metal Oxide Semiconductor (CMOS) is Quantum-dot Cellular Automata (QCA). Test generation is an unavoidable process in the CMOS design flow. This possibility of test generation must be explored and applied to the QCA as the QCA is a novel and nanoscale technology. Therefore, in this paper, the test generation process is explored and implemented for QCA combinational circuits. The FAN (A Fanout Oriented) Automatic Test pattern Generator (ATPG) algorithm is extended for QCA (FANQ). The proposed FANQ ATPG is developed for faults caused by Multiple Missing Cells (MMC) along with single missing cell defect in QCA primitives and circuits which is not reported in earlier QCA based ATPG. The previously proposed testing properties and testability measures are incorporated in the FANQ ATPG for its effectiveness. The generated test vectors are compacted and tested on previously synthesized, QCA-oriented Microelectronics Center for North Carolina (MCNC) benchmark circuits. Further, the generated test vectors are also validated at the layout level to demonstrate the correctness of ATPG. The proposed ATPG for QCA combinational circuits required fewer test vectors for the stuck at fault model compared to the available QCA ATPG.

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Section: B Testability Measuresmentioning

confidence: 99%