PCR is a well-understood and established laboratory technique often used in molecular diagnostics. Huge experience has been accumulated over the last years regarding the design of PCR assays and their set-up, including in-depth troubleshooting to obtain the optimal PCR assay for each purpose. Here we report a PCR troubleshooting that came up with a surprising result never observed before. With ...

Troubleshooting is the process of diagnosing and repairing a system that is behaving abnormally. Diagnostic and repair actions may incur costs, and traditional troubleshooting algorithms aim to minimize the costs incurred until the system is fixed. We propose an anticipatory troubleshooting algorithm, which is able to reason about both current and future failures. To reason about failures over ...

Troubleshooting is the process of diagnosing and repairing a system that behaving abnormally. It involves performing various diagnostic repair actions. Performing these actions may incur costs, traditional troubleshooting algorithms aim to minimize costs incurred until fixed. Prognosis deals with predicting future failures. We propose incorporate prognosis diagnosis techniques solve problems. T...

Analysis of a real case of software troubleshooting made it clear that probabilistic models, or Bayesian networks are suitable for modeling software troubleshooting processes in today’s computing environments. As a way to support software troubleshooting by reusing skillful support engineers’ expertise, I propose to use Bayesian networks and probabilistic reasoning for case-based retrieval. The...

When troubleshooting malfunctioning technical equipment, the task is to locate faults and make repairs until the equipment functions properly again. The AO* algorithm can be used to find troubleshooting strategies that are optimal in the sense that the expected cost of repair is minimal. We have adapted the AO* algorithm for troubleshooting in the automotive domain with limited time. We propose...

In decision-theoretic troubleshooting [5,2], we try to find a cost efficient repair strategy for a malfunctioning device described by a formal model. The need to schedule repair actions under uncertainty has required the researchers to use an appropriate knowledge representation formalism, often a probabilistic one. The troubleshooting problem has received considerable attention over the past t...

Jason Flinn is an associate professor of computer science and engineering at the University of Michigan. His research interests include operating systems, distributed systems, storage, and mobile computing. [email protected] Complex software systems are difficult to configure and manage . When problems inevitably arise, operators spend considerable time troubleshooting those problems by identify...

We present an approach to efficiently generating an inspection strategy for fault diagnosis. We extend the traditional troubleshooting framework to model nonperfect repair actions, and we include questions. Questions are troubleshooting steps that do not aim at repairing the device, but merely are performed to capture information about the failed equipment, and thereby ease the identification a...

We present an approach to efficiently generating an inspection strategy for fault diagnosis. We extend the traditional troubleshooting framework to model nonperfect repair actions, and we include questions. Questions are troubleshooting steps that do not aim at repairing the device, but merely are performed to capture information about the failed equipment, and thereby ease the identification a...