The advantage to "one test at a time" fault diagnosis is its ability to implicate the components of complicated defect behaviors. The disadvantage is the large size and opacity of the diagnostic answer. In this paper, we address the problems of per-test diagnosis by improving the candidate matching, introducing scoring and ranking techniques, and by developing a method to translate the results into common defect scenarios. Our experimental results on simulated defects indicate that not only are the results improved on complex behaviors, but by considering passing test results we improve a common case where per-test algorithms can perform significantly worse than traditional diagnosis algorithms. Finally, our method of candidate analysis provides a way to bridge the per-test approach with traditional model-based fault diagnosis.

The foremost problem in VLSI fault diagnosis is the problem of data: there's simply too much of it. Circuits are large and contain enormous numbers of faults of many types. Full-response fault dictionaries are too large for practical or quick diagnosis, but pass-fail dictionaries often do not provide adequate resolution. The goal of this paper is to examine different sets of diagnostic data, determine the utility of each, and investigate ways of drastically reducing the data requirements for fault diagnosis. In doing so we introduce a new fault signature type, and begin to develop the idea of low-precision fault diagnosis in which useful diagnoses are obtained with a minimum of data and computation.

In this paper we present a design for IEEE 1149.1 Test Access Port (TAP) controllers that is based on a practical reuse methodology. While the basic use and core functionality of TAP controllers are standardized, the RTL structure and user refinements of TAPs can vary widely leading to incompatibilities and difficulties in reusing TAP controller IP across designs and between DFT suppliers. Upon study, we find that the TAP controller is an ideal candidate for reuse. From the definitions and guidelines of the IEEE Standard we can construct a core architecture of required modules and fully define their interfaces. With the addition of a few simple usage and design guidelines, we can then define an "open architecture" TAP controller that facilitates rapid, automatic customization with a library of modular enhancements.

I/sub DDQ/ diagnosis is an important part of the Failure Analysis toy box, but it often requires substantial guesswork and intuition, especially when trying to divine the proper pass-fail threshold for the correct diagnostic result. This paper describes clustering and probability assignment algorithms designed to eliminate this guesswork by automatically determining diagnostic pass-fail thresholds, while using probabilistic techniques to allow for reasonable noise and error. We report the result of using these techniques on some of the failing chips from the Sematech experiment. The system describe first identifies appropriate thresholds and then pinpoints the correct diagnosis without requiring manual intervention and without requiring that the observed I/sub DDQ/ behavior perfectly matches the predicted I/sub DDQ/ behavior. The paper also discusses the use of information produced by inductive fault analysis and specialized fault simulation as part of the diagnosis process.

Previously-proposed strategies for VLSI fault diagnosis have suffered from a variety of self-imposed limitations. Some techniques are limited to a specific fault model, and many will fail in the face of any unmodeled behavior or unexpected data. Others apply ad-hoc or arbitrary scoring mechanisms to fault candidates, making the results difficult to interpret or to compare with the results from other algorithms. This paper outlines an approach to fault diagnosis that is robust, comprehensive, extendable, and practical. By introducing a probabilistic framework for diagnostic prediction, it is designed to incorporate disparate diagnostic algorithms, different sets of data, and a mixture of fault models into a single diagnostic result. Results from diagnosis experiments on a Hewlett-Packard ASIC and FIB inserted defects are presented.

Automated fault diagnosis based on the stuck-at fault model is not always effective. This paper presents practical experiences in applying a bridging fault based diagnosis technique to a TI ASIC design. Results are presented for units into which known bridging defects have been introduced via a focused ion beam (FIB) machine.

Successful failure analysis requires accurate fault diagnosis. This paper presents a method for diagnosing bridging faults that improves on previous methods. The new method uses single stuck-at fault signatures, produces accurate and precise diagnoses, and takes into account imperfect fault modeling; it accomplishes this by introducing the concepts of match restriction, match requirement, and match ranking.

Effective bridging fault diagnosis requires reducing the (/sub 2//sup n/) number of bridging faults to a handful of candidates. A preliminary step can reduce the O(n/sup 2/) candidates to a manageable O(n) candidates by using layout information to eliminate those bridging faults that are very unlikely to be shorted together. This step removes from consideration those faults that match the fault signature but are physically impossible. However, sometimes-perhaps due to issues of intellectual property or because the degree of information stored about a circuit changes over its lifecycle-the physical design of the circuit is not available, and the number of nodes is too large to explicitly consider all pairs. In this paper we present two ways to provide successful diagnoses without access to physical information. The second method produces optimal diagnoses under our ranking criteria. Either technique can be used in conjunction with information extracted from the physical design to allow for diagnoses of much larger circuits than previously possible.

Physical defects cause behaviors unmodeled by even the best fault simulators, which complicates predictive diagnosis. This paper reports on a diagnosis procedure that uses modified composite signatures constructed from single stuck-at information combined with a lexicographic matching and ranking algorithm. The diagnosis procedure is used to perform high-quality bridging fault diagnosis for more than 400,000 diagnostic experiments involving dropping or adding behaviors from the simulations of faulty circuits.

Such interactive, distributed multimedia applications as shared whiteboards, group editors, and simulations require reliable concurrent multicast services, i.e., the reliable dissemination of information from multiple sources to all the members of a group. Furthermore, it makes sense to offer that service on top of the increasingly available IP multicast service, which offers unreliable multicasting. This paper establishes that concurrent reliable multicasting over the Internet should be based on reliable multicast protocols based on a shared acknowledgment tree. First, we show that organizing the receivers of a reliable multicast group into an acknowledgment tree and using NAK-avoidance with periodic polling in local groups inside such a tree provides the highest maximum throughput among all classes of reliable multicast protocols proposed to date. Second, we introduce Lorax, which demonstrates the viability of implementing a reliable multicasting approach in the Internet based on acknowledgment trees in a scalable manner. Lorax is the first known protocol that constructs and maintains a single acknowledgment tree for reliable concurrent multicasting, eliminates the need to maintain an acknowledgment tree for each source of a reliable multicast group, and can be used in combination with any of several tree-based reliable multicast protocols proposed to date.

Precise failure analysis requires accurate fault diagnosis. A previously proposed method for diagnosing bridging faults using single stuck-at dictionaries was applied only to small circuits, produced large and imprecise diagnoses, and did not take into account the Byzantine Generals Problem for bridging faults. We analyze the original technique and improve it by introducing the concepts of match restriction, match requirement, and failure recovery. Our new technique, which requires no information other than that used by standard stuck-at methods, produces diagnoses that are an order of magnitude smaller than those produced by the original technique and produces many fewer misleading diagnoses than that of traditional stuck-at diagnosis.