Exact stuck-at fault classification in presence of unknowns

2013 22nd Asian Test Symposium

et al. 2013

Self Cite

Unknown (X) values in a circuit impair test quality and increase test costs. Classical n-valued algorithms for fault simulation and ATPG, which typically use a three-or four-valued logic for the good and faulty circuit, are in principle pessimistic in presence of X-values and cannot accurately compute the achievable fault coverage.In partial scan or pipelined circuits, X-values originate in non-scan flip-flops. These circuits are tested using multi-cycle tests. Here we present multi-cycle test generation techniques for circuits with X-values due to partial scan or other X-sources. The proposed techniques have been integrated into a multi-cycle ATPG framework which employs formal Boolean and quantified Boolean (QBF) satisfiability techniques to compute the possible signal states in the circuit accurately. Efficient encoding of the problem instance ensures reasonable runtimes.We show that in presence of X-values, the detection of stuck-at faults requires not only exact formal reasoning in a single cycle, but especially the consideration of multiple cycles for excitation of the fault site as well as propagation and controlled reconvergence of fault effects.For the first time, accurate deterministic ATPG for multi-cycle test application is supported for stuck-at faults. Experiments on ISCAS'89 and industrial circuits with X-sources show that this new approach increases the fault coverage considerably.

Section: Accurate Multi-cycle Atpg Algorithmmentioning

confidence: 98%

Section: Accurate Multi-cycle Atpg Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Accurate Multi-cycle ATPG in Presence of X-Values

Erb

Kochte

2013 22nd Asian Test Symposium

et al. 2013

Self Cite

“…More accurate or even fully accurate fault simulation can be performed even for large circuits by a combination of heuristics and SAT reasoning and allows a significant increase of fault coverage [22][23][24]. In principle, both logic and fault simulation in presence of X-values are NP-complete problems.…”

Section: Unknown Values In Circuit Testmentioning

confidence: 99%

Modeling Unknown Values in Test and Verification

Becker

Formal Modeling and Verification of Cyber-Physical Systems

Scholl

et al. 2015

Self Cite

Abstract.With increasing complexities and a component-based design style the handling of unknown values (e. g., at the interface of components) becomes more and more important in electronic design automation (EDA) and production processes. Tools are required that allow an accurate modeling of unknowns in combination with algorithms balancing exactness of representation and efficiency of calculation. In the following, state-ofthe-art approaches are described that enable an efficient and successful handling of unknown values using formal techniques in the areas of Test and Verification.

“…The recent progress in SAT solvers enables the exact reasoning about fault detection in presence of X-values even for larger circuits [Hillebrecht et al 2012]. This work proposes a formal method to exactly compute the stuck-at and transition-delay fault coverage of a test set in presence of X-values.…”

Section: A:3mentioning

confidence: 99%

Exact Logic and Fault Simulation in Presence of Unknowns

Erb

Kochte

ACM Trans. Des. Autom. Electron. Syst.

et al. 2014

Self Cite

Logic and fault simulation are essential techniques in electronic design automation. The accuracy of standard simulation algorithms is compromised by unknown or X-values. This results in a pessimistic overestimation of X-valued signals in the circuit and a pessimistic underestimation of fault coverage. This work proposes efficient algorithms for combinational and sequential logic as well as for stuck-at and transition-delay fault simulation that are free of any simulation pessimism in presence of unknowns. The SAT-based algorithms exactly classifiy all signal states. During fault simulation, each fault is accurately classified as either undetected, definitely detected, or possibly detected. The pessimism with respect to unknowns present in classic algorithms is thoroughly investigated in the experimental results on benchmark circuits. The applicability of the proposed algorithms is demonstrated on larger industrial circuits. The results show that, by accurate analysis, the number of detected faults can be significantly increased without increasing the test-set size. Preprint General Copyright NoticeThis article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. This is the author's "personal copy" of the final, accepted version of the paper published by ACM.c 2014 ACM. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Logic and fault simulation are essential techniques in electronic design automation. The accuracy of standard simulation algorithms is compromised by unknown or X-values. This results in a pessimistic overestimation of X-valued signals in the circuit, and a pessimistic underestimation of fault coverage. A Exact Logic and Fault Simulation in Presence of UnknownsThis work proposes efficient algorithms for combinational and sequential logic as well as for stuck-at and transition-delay fault simulation which are free of any simulation pessimism in presence of unknowns. The SAT-based algorithms exactly classifiy all signal states. During fault simulation, each fault is accurately classified as either undetected, definitely detected or possibly detected.The pessimism w. r. t. unknowns present in classic algorithms is thoroughly investigated in the experimental results on benchmark circuits. The applicability of the proposed algorithms is demonstrated on larger industrial circuits. The results show that by accurate analysis the number of de...