Dominik Erb

Accurate QBF-based test pattern generation in presence of unknown values

Unknown (X) values may emerge during the design process as well as during system operation and test application. Sources of X-values are for example black boxes, clock-domain boundaries, analog-to-digital converters, or uncontrolled or uninitialized sequential elements. To compute a detecting pattern for a given stuck-at fault, well defined logic values are required both for fault activation as well as for fault effect propagation to observing outputs. In presence of X-values, classical test generation algorithms, based on topological algorithms or formal Boolean satisfiability (SAT) or BDD-based reasoning, may fail to generate testing patterns or to prove faults untestable. This work proposes the first efficient stuck-at fault ATPG algorithm able to prove testability or untestability of faults in presence of X-values. It overcomes the principal inaccuracy and pessimism of classical algorithms when X-values are considered. This accuracy is achieved by mapping the test generation problem to an instance of quantified Boolean formula (QBF) satisfiability. The resulting fault coverage improvement is shown by experimental results on ISCAS benchmark and larger industrial circuits.

Efficient SMT-based ATPG for interconnect open defects

Interconnect opens are known to be one of the predominant defects in nanoscale technologies. However, automatic test pattern generation for open faults is challenging, because of their rather unstable behaviour and the numerous electric parameters which need to be considered. Thus, most approaches try to avoid accurate modeling of all constraints and use simplified fault models in order to detect as many faults as possible or make assumptions which decrease both complexity and accuracy. This paper presents a new SMT-based approach which for the first time supports the Robust Enhanced Aggressor Victim model without restrictions and handles oscillations. It is combined with the first open fault simulator fully supporting the Robust Enhanced Aggressor Victim model and thereby accurately considering unknown values. Experimental results show the high efficiency of the new method outperforming previous approaches by up to two orders of magnitude.

Exact Logic and Fault Simulation in Presence of Unknowns

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.

Test pattern generation in presence of unknown values based on restricted symbolic logic

Test generation algorithms based on standard n-valued logic algebras are pessimistic in presence of unknown (X) values, overestimate the number of signals with X-values and underestimate fault coverage.

Mixed 01X-RSL-Encoding for fast and accurate ATPG with unknowns

Unknown (X) values in a design introduce pessimism in conventional test generation algorithms, which results in a loss of fault coverage. This pessimism is reduced by a more accurate modeling and analysis. Unfortunately, accurate analysis techniques highly increase runtime and limit scalability. One promising technique to prevent high runtimes while still providing high accuracy is the use of restricted symbolic logic (RSL). However, also pure RSL-based algorithms reach their limits as soon as millon gate circuits need to be processed. In this paper, we propose new ATPG techniques to overcome such limitations. An efficient hybrid encoding combines the accuracy of RSL-based modeling with the compactness of conventional threevalued encoding. A low-cost two-valued SAT-based untestability check is able to classify most untestable faults with low runtime. An incremental and event-based accurate fault simulator is introduced to reduce fault simulation effort. The experiments demonstrate the effectiveness of the proposed techniques. On average, over 99.3% of the considered faults are accurately classified. Both the number of aborts and the total runtime are significantly reduced compared to the state-of-the-art pure RSL-based algorithm. For circuits up to a million gates, the fault coverage could be increased considerably compared to a state-of-the-art commercial tool with very competitive runtimes.

Accurate CEGAR-based ATPG in presence of unknown values for large industrial designs

Unknown values emerge during the design and test generation process as well as during later test application and system operation. They adversely affect the test quality by reducing the controllability and observability of internal circuit structures - resulting in a loss of fault coverage. To handle unknown values, conventional test generation algorithms as used in state-of-the-art commercial tools, rely on n-valued algebras. However, n-valued algebras introduce pessimism as soon as X-values reconverge. Consequently, these algorithms fail to compute the accurate result. This paper focuses on a new highly incremental CEGAR-based algorithm that overcomes these limitations and hence is completely accurate in presence of unknown values. It relies on a modified SAT-solver tailored for this specific problem. The experimental results for circuits with up to 2 400 000 gates show that this combination allows high accuracy and high scalability at the same time. Compared to a state-of-the-art commercial tool, the fault coverage could be increased significantly. Furthermore, the runtime is reduced remarkably compared to a QBF-based encoding of the problem.

Improving test pattern generation in presence of unknown values beyond restricted symbolic logic

Test generation algorithms considering unknown (X) values are pessimistic if standard n-valued logic algebras are used. This results in an overestimation of the number of signals with X-values and an underestimation of the fault coverage. In contrast, algorithms based on quantified Boolean formula (QBF), are accurate in presence of X-values but have limits with respect to runtime, scalability and robustness. Recently, an algorithm based on restricted symbolic logic (RSL) has been presented which is more accurate than classical three-valued logic and faster than QBF. Nonetheless, this RSL-based approach is still pessimistic and is unable to detect all testable faults. Additionally, it does not allow the accurate identification of untestable faults. In this paper, we improve test pattern generation based on RSL in two directions in order to reduce the accuracy-gap to QBF further. First, we present techniques to go beyond the accuracy of RSL when generating test patterns. Second, we include a check which is able to accurately identify untestable faults. Experimental results show the high efficiency of the proposed method. It is able to classify almost all faults - either by generating a test pattern or proving untestability.

Circuit Parameter Independent Test Pattern Generation for Interconnect Open Defects

Open defects such as interconnect opens are known to be one of the predominant defects in nanoscale technologies. Yet, test pattern generation for open defects is challenging because of the high number of parameters which need to be considered. Additionally, the assumed values of these parameters may vary due to process variations reducing fault coverage of a test set generated under this assumption. This paper presents a new ATPG approach for circuit Parameter independent (CPI) tests. In addition a definition of oscillation free CPI tests is given. The generated tests are robust against process variations affecting the influence of neighboring interconnects as well as trapped charge and prohibit oscillating behavior. Experimental results show the high efficiency of the new approach, generating CPI tests for circuits with over 500k nonequivalent faults and several thousand aggressors.

Multi-cycle Circuit Parameter Independent ATPG for interconnect open defects

Interconnect opens are known to be one of the predominant defects in nanoscale technologies. Generating tests to detect such defects is challenging due to the need to accurately determine the coupling capacitances between the open net and its aggressors and fix the state of these aggressors during test. Process variations cause deviations from assumed values of circuit parameters thus potentially invalidating tests generated with assumed circuit parameters. Additionally, recent investigation using test chips showed that the steady state voltage on open nets may drift slowly with the application of circuit inputs and can be different at different nets.

Accurate QBF-Based Test Pattern Generation in Presence of Unknown Values

Unknown (X) values may emerge during the design process as well as during system operation and test application. Sources of X-values are for example black boxes, clock-domain boundaries, analog-to-digital converters, or uncontrolled or uninitialized sequential elements.