Approaches to test set generation using binary decision diagrams

This research pursues the use of powerful BDD-based functional circuit analysis to evaluate some approaches to test set generation. Functional representations of the circuit allow the measurement of information about faults that is not directly available through circuit simulation methods, such as probability of random detection and test-space overlap between faults. I have created a software tool that performs experiments to make such measurements and augments existing test generation strategies with this new information. Using this tool, I explored the relationship of fault model difficulty to test set length through fortuitous detection, and I experimented with the application of function-based methods to help reconcile the traditionally opposed goals of making test sets that are both smaller and more effective

VLSI Testing and Test Power

This paper first reviews the basics of VLSI testing, focusing on test generation and design for testability. Then it discusses the impact of test power in scan testing, and highlights the need for low-power VLSI testing.2011 International Green Computing Conference and Workshops (IGCC 2011), July 25-28, 2011, Orlando, FL, US

Modeling defective part level due to static and dynamic defects based upon site observation and excitation balance

Manufacture testing of digital integrated circuits is essential for high quality. However, exhaustive testing is impractical, and only a small subset of all possible test patterns (or test pattern pairs) may be applied. Thus, it is crucial to choose a subset that detects a high percentage of the defective parts and produces a low defective part level. Historically, test pattern generation has often been seen as a deterministic endeavor. Test sets are generated to deterministically ensure that a large percentage of the targeted faults are detected. However, many real defects do not behave like these faults, and a test set that detects them all may still miss many defects. Unfortunately, modeling all possible defects as faults is impractical. Thus, it is important to fortuitously detect unmodeled defects using high quality test sets. To maximize fortuitous detection, we do not assume a high correlation between faults and actual defects. Instead, we look at the common requirements for all defect detection. We deterministically maximize the observations of the leastobserved sites while randomly exciting the defects that may be present. The resulting decrease in defective part level is estimated using the MPGD model. This dissertation describes the MPGD defective part level model and shows how it can be used to predict defective part levels resulting from static defect detection. Unlike many other predictors, its predictions are a function of site observations, not fault coverage, and thus it is generally more accurate at high fault coverages. Furthermore, its components model the physical realities of site observation and defect excitation, and thus it can be used to give insight into better test generation strategies. Next, we investigate the effect of additional constraints on the fortuitous detection of defects-specifically, as we focus on detecting dynamic defects instead of static ones. We show that the quality of the randomness of excitation becomes increasingly important as defect complexity increases. We introduce a new metric, called excitation balance, to estimate the quality of the excitation, and we show how excitation balance relates to the constant τ in the MPGD model

Using ordered partial decision diagrams for manufacture test generation

Because of limited tester time and memory, a primary goal of digital circuit manufacture test generation is to create compact test sets. Test generation programs that use Ordered Binary Decision Diagrams (OBDDs) as their primary functional representation excel at this task. Unfortunately, the use of OBDDs limits the application of these test generation programs to small circuits. This is because the size of the OBDD used to represent a function can be exponential in the number of the function's switching variables. Working with these functions can cause OBDD-based programs to exceed acceptable time and memory limits. This research proposes using Ordered Partial Decision Diagrams (OPDDs) instead as the primary functional representation for test generation systems. By limiting the number of vertices allowed in a single OPDD, complex functions can be partially represented in order to save time and memory. An OPDD-based test generation system is developed and techniques which improve its performance are evaluated on a small benchmark circuit. The new system is then demonstrated on larger and more complex circuits than its OBDD-based counterpart allows

High Quality Compact Delay Test Generation

Delay testing is used to detect timing defects and ensure that a circuit meets its timing specifications. The growing need for delay testing is a result of the advances in deep submicron (DSM) semiconductor technology and the increase in clock frequency. Small delay defects that previously were benign now produce delay faults, due to reduced timing margins. This research focuses on the development of new test methods for small delay defects, within the limits of affordable test generation cost and pattern count. First, a new dynamic compaction algorithm has been proposed to generate compacted test sets for K longest paths per gate (KLPG) in combinational circuits or scan-based sequential circuits. This algorithm uses a greedy approach to compact paths with non-conflicting necessary assignments together during test generation. Second, to make this dynamic compaction approach practical for industrial use, a recursive learning algorithm has been implemented to identify more necessary assignments for each path, so that the path-to-test-pattern matching using necessary assignments is more accurate. Third, a realistic low cost fault coverage metric targeting both global and local delay faults has been developed. The metric suggests the test strategy of generating a different number of longest paths for each line in the circuit while maintaining high fault coverage. The number of paths and type of test depends on the timing slack of the paths under this metric. Experimental results for ISCAS89 benchmark circuits and three industry circuits show that the pattern count of KLPG can be significantly reduced using the proposed methods. The pattern count is comparable to that of transition fault test, while achieving higher test quality. Finally, the proposed ATPG methodology has been applied to an industrial quad-core microprocessor. FMAX testing has been done on many devices and silicon data has shown the benefit of KLPG test

Fault simulation and test generation for small delay faults

Delay faults are an increasingly important test challenge. Traditional delay fault models are incomplete in that they model only a subset of delay defect behaviors. To solve this problem, a more realistic delay fault model has been developed which models delay faults caused by the combination of spot defects and parametric process variation. According to the new model, a realistic delay fault coverage metric has been developed. Traditional path delay fault coverage metrics result in unrealistically low fault coverage, and the real test quality is not reflected. The new metric uses a statistical approach and the simulation based fault coverage is consistent with silicon data. Fast simulation algorithms are also included in this dissertation. The new metric suggests that testing the K longest paths per gate (KLPG) has high detection probability for small delay faults under process variation. In this dissertation, a novel automatic test pattern generation (ATPG) methodology to find the K longest testable paths through each gate for both combinational and sequential circuits is presented. Many techniques are used to reduce search space and CPU time significantly. Experimental results show that this methodology is efficient and able to handle circuits with an exponential number of paths, such as ISCAS85 benchmark circuit c6288. The ATPG methodology has been implemented on industrial designs. Speed binning has been done on many devices and silicon data has shown significant benefit of the KLPG test, compared to several traditional delay test approaches

High Quality Test Generation Targeting Power Supply Noise

Delay test is an essential structural manufacturing test used to determine the maximal frequency at which a chip can run without incurring any functional failures. The central unsolved challenge is achieving high delay correlation with the functional test, which is dominated by power supply noise (PSN). Differences in PSN between functional and structural tests can lead to differences in chip operating frequencies of 30% or more. Pseudo functional test (PFT), based on a multiple-cycle clocking scheme, has better PSN correlation with functional test compared with traditional two-cycle at-speed test. However, PFT is vulnerable to under-testing when applied to delay test. This work aims to generate high quality PFT patterns, achieving high PSN correlation with functional test. First, a simulation-based don’t-care filling algorithm, Bit-Flip, is proposed to improve the PSN for PFT. It relies on randomly flipping a group of bits in the test pattern to explore the search space and find patterns that stress the circuits with the worst-case, but close to functional PSN. Experimental results on un-compacted patterns show Bit-Flip is able to improve PSN as much as 38.7% compared with the best random fill. Second, techniques are developed to improve the efficiency of Bit-Flip. A set of partial patterns, which sensitize transitions on critical cells, are pre-computed and later used to guide the selection of bits to flip. Combining random and deterministic flipping, we achieve similar PSN control as Bit-Flip but with much less simulation time. Third, we address the problem of automatic test pattern generation for extracting circuit timing sensitivity to power supply noise during post-silicon validation. A layout-aware path selection algorithm selects long paths to fully span the power delivery network. The selected patterns are intelligently filled to bring the PSN to a desired level. These patterns can be used to understand timing sensitivity in post-silicon validation by repeatedly applying the path delay test while sweeping the PSN experienced by the path from low to high. Finally, the impacts of compression on power supply noise control are studied. Illinois Scan and embedded deterministic test (EDT) patterns are generated. Then Bit-Flip is extended to incorporate the compression constraints and applied to compressible patterns. The experimental results show that EDT lowers the maximal PSN by 24.15% and Illinois Scan lowers it by 2.77% on un-compacted patterns

Power supply noise in delay testing

As technology scales into the Deep Sub-Micron (DSM) regime, circuit designs have become more and more sensitive to power supply noise. Excessive noise can significantly affect the timing performance of DSM designs and cause non-trivial additional delay. In delay test generation, test compaction and test fill techniques can produce excessive power supply noise. This will eventually result in delay test overkill. To reduce this overkill, we propose a low-cost pattern-dependent approach to analyze noise-induced delay variation for each delay test pattern applied to the design. Two noise models have been proposed to address array bond and wire bond power supply networks, and they are experimentally validated and compared. Delay model is then applied to calculate path delay under noise. This analysis approach can be integrated into static test compaction or test fill tools to control supply noise level of delay tests. We also propose an algorithm to predict transition count of a circuit, which can be applied to control switching activity during dynamic compaction. Experiments have been performed on ISCAS89 benchmark circuits. Results show that compacted delay test patterns generated by our compaction tool can meet a moderate noise or delay constraint with only a small increase in compacted test set size. Take the benchmark circuit s38417 for example: a 10% delay increase constraint only results in 1.6% increase in compacted test set size in our experiments. In addition, different test fill techniques have a significant impact on path delay. In our work, a test fill tool with supply noise analysis has been developed to compare several test fill techniques, and results show that the test fill strategy significant affect switching activity, power supply noise and delay. For instance, patterns with minimum transition fill produce less noise-induced delay than random fill. Silicon results also show that test patterns filled in different ways can cause as much as 14% delay variation on target paths. In conclusion, we must take noise into consideration when delay test patterns are generated