The automotive industry has to deal with an increasing amount of electronics in today's vehicles. This paper describes the advantages of structural tests during in-field system test, reusing existing test data and on-chip structures. Demonstration is the embedded test of an ASIC within an automotive control unit, utilizing manufacturing scan-tests.

Unknown or X-values during test applications may originate from uncontrolled sequential cells or macros, from clock or A/D boundaries, or from tristate logic. The exact identification of X-value propagation paths in logic circuits is crucial in logic simulation and fault simulation. In the first case, it enables the proper assessment of expected responses and the effective and efficient handling of X-values during test response compaction. In the second case, it is important for a proper assessment of fault coverage of a given test set and consequently influences the efficiency of test pattern generation. The commonly employedn-valued logic simulation evaluates the propagation of X-values only pessimistically, i.e., the X-propagation paths found byn-valued logic simulation are a superset of the actual propagation paths. This paper presents an efficient method for overcoming this pessimism and for determining accurately the set of signals that carry an X-value for an input pattern. As examples, it investigates the influence of this pessimism on the two applications, X-masking and stuck-at fault coverage assessment. The experimental results on benchmark and industrial circuits assess the pessimism of classic algorithms and show that these algorithms significantly overestimate the signals with X-values. The experiments show that overmasking of test data during test compression can be reduced by an accurate analysis. In stuck-at fault simulation, the coverage of the test set is increased by the proposed algorithm without incurring any overhead.

In-field diagnosability of electronic components in larger systems such as automobiles becomes a necessity for both customers and system integrators. Traditionally, functional diagnosis is applied during integration and in workshops for in-field failures or break-downs. However, functional diagnosis does not yield sufficient coverage to allow for short repair times and fast reaction on systematic failures in the production. Structural diagnosis could yield the desired coverage, yet recent built-in architectures which could be reused in the field either do not reveal diagnostic information or necessitate dedicated test schemes. The paper at hand closes this gap with a new built-in test method for autonomous in-field testing and in-field diagnostic data collection. The proposed Built-In Self-Diagnosis method (BISD) is based on the standard BIST architecture and can seamlessly be integrated with recent, commercial DfT techniques. Experiments with industrial designs show that its overhead is marginal and its structural diagnostic capabilities are comparable to those of external diagnosis on high-end test equipment.

Networks-on-Chip (NoCs) are implicitly fault tolerant due to their inherent redundancy. They can overcome defective cores, links and switches. As a side effect, yield is increased at the cost of reduced performability. In this paper, a new diagnosis method based on the standard flow of industrial volume testing is presented, which is able to identify the intact functions rather than providing only a pass/fail result for the complete switch. The new method combines for the first time the precision of structural testing with information on the functional behavior in the presence of defects to determine the unaffected switch functions and use partially defective NoC switches. According to the experimental results, this improves the performability of NoCs as more than 61\% of defects only impair one switch port. Unlike previous methods for implementing fault tolerant switches, the developed technique does not impose any additional area overhead and is compatible with any switch design.

Embedded testing, built-in self-test and methods for test compression rely on efficient test response compaction. Often, a circuit under test contains sources of unknown values (X), uninitialized memories for instance. These X values propagate through the circuit and may spoil the response signatures. The standard way to overcome this problem is X-masking. Outputs which carry an X value are usually determined by logic simulation. In this paper, we show that the amount of Xs is significantly overestimated, and in consequence outputs are over masked, too. An efficient way for the exact computation of output Xs is presented for the first time. The resulting X-masking promises significant gains with respect to test time, test volume and fault coverage.

Built-In Self-Test (BIST) is less often applied to random logic than to embedded memories due to the following reasons: Firstly, for a satisfiable fault coverage it may be necessary to apply additional deterministic patterns, which cause additional hardware costs. Secondly, the BIST-signature reveals only poor diagnostic information. Recently, the first issue has been addressed successfully. The paper at hand proposes a viable, effective and cost efficient solution for the second problem. The paper presents a new method for Built-in Self-Diagnosis (BISD). The core of the method is an extreme response compaction architecture, which for the first time enables an autonomous on-chip evaluation of test responses with negligible hardware overhead. The key advantage of this architecture is that all data, which is relevant for a subsequent diagnosis, is gathered during just one test session. The BISD method comprises a hardware scheme, a test pattern generation approach and a diagnosis algorithm. Experiments conducted with industrial designs substantiate that the additional hardware overhead introduced by the BISD method is on average about 15% of the BIST area, and the same diagnostic resolution can be obtained as for external testing.

Optimizing bandwidth by compression and compaction always has to solve the trade-off between input bandwidth reduction and output bandwidth reduction. Recently it has been shown that splitting scan chains into shorter segments and compacting the shift data outputs into a singleparity bit reduces the test response data to one bit per cycle without affecting fault coverage and diagnostic resolution if the compactor's structure is included into the ATPG process.This test data reduction at the output side comes with challenges at the input side. The bandwidth requirement grows due to the increased number of chains and due to a drastically decreased amount of don't care values in the test patterns. The paper at hand presents a new iterative approach to test set encoding which optimizes bandwidth on both input and output side while keeping the diagnostic resolution and fault coverage. Experiments with industrial designs demonstrate that test application time, test data volume and diagnostic resolution are improved at the same time and for most designs testing with a bandwidth of three bits per cycle is possible.

An effective technique to save power during scan based test is to switch off unused scan chains. The results obtained with this method strongly depend on the mapping of scan flip-flops into scan chains, which determines how many chains can be deactivated per pattern.

Keeping diagnostic resolution as high as possible while maximizing the compaction ratio is subject to research since the advent of embedded test. In this paper, we present a novel scan design methodology to maximize diagnostic resolution when compaction is employed. The essential idea is to consider the diagnostic resolution during the clustering of scan elements to scan chains. Our methodology does not depend on a fault model and is helpful with any type of compactor. A linear time heuristic is presented to solve the scan chain clustering problem. We evaluate our approach for industrial and academic benchmark circuits. It turns out to be superior to both random and to layout driven scan chain clustering. The methodology is applicable to any gate-level design and fits smoothly into an industrial design flow.