Troubleshooting: When Modeling Is the Trouble
نویسندگان
چکیده
TROUBLESHOOTING WHEN MODELING IS THE TROUBLE Paper type: Full paper Track: Engineering P . Dague Mailing address : Paris IBM Scientific Center 36 Ave R . Poincare 75116 Paris France Telephone: 33 (1) 45 05 14 00 P. 27-40 Address: earn/ bitnet dague at frpoi l 1 P . Deves Electronique Serge Dassault 55 Quai M. Dassault S , Cloud 92214 France O. Raiman Paris IBM Scientific Center 36 Ave R . Poincare Paris 75116 France When troubleshooting, finding components where changes in behavior occur only guides the search . In a misbehaving device, a correct component can indeed change its behavior. Distinguishing faulty components from correct ones requires modeling all possible correct behaviors of components. For analog circuits, there is a lack ofnumerical models anda lack of information on essentialparameters . Therefore, modeling becomes quickly the real trouble. Under the assumption that "a defect leads to significant change in the behavior of a device", we show that Qualitative Reasoning is a solution . To exploit the above assumption, order of magnitude reasoning is used for modeling and defining a strategy . Experience with the expert system DEDAIE has .shown that this assumption applies to a wide class of cases, and that Qualitative Reasoning can be usedfor a real size application . Submitted to AAAI-87 (also submitted to IJCAI-87) Topics: Engineering Problem Solving Troubleshooting Commonsense Reasoning Qualitative Reasoning
منابع مشابه
Juggling the Jigsaw: Towards Automated Problem Inference from Network Trouble Tickets
This demo will present NetSieve [1], a system to do automated problem inference from network trouble tickets. Trouble tickets are diaries comprising fixed fields and free-form text written by operators while troubleshooting a problem. Unfortunately, while they carry valuable information for network management, analyzing them to do problem inference is extremely difficult—fixed fields are often ...
متن کاملError Prevention and Troubleshooting
This chapter summarizes the common errors haunting the beginner modelers. Modeling is a tricky, error-inviting business, as you would probably agree through doing the homework problems. The errors can be as small as a typo, or as big as capturing the relationships between quantities incorrectly (i.e. making a wrong flowchart to start with). Some errors are easily detected and reported by Berkel...
متن کاملA Modeling Framework for Troubleshooting Automotive Systems
This paper presents a novel framework for modeling the troubleshooting process for automotive systems such as trucks and buses. We describe how a diagnostic model of the troubleshooting process can be created using event-driven nonstationary dynamic Bayesian networks. Exact inference in such a model is in general not practically possible. Therefore we evaluate different approximate methods for ...
متن کاملPingmesh: A Large-Scale System for Data Center Network Latency Measurement and Analysis – Public Review
Fast troubleshooting of network problems presents considerable challenges for the network operations team in production systems. In many cases, it is not obvious that a system issue such as slow response from a server or an unreachable server, is caused by a network problem or not in the first place. Today most of this detection and diagnosis is semi-manual and time consuming, and is particular...
متن کاملA Proposal to Combine Probabilistic Reasoning with Case-Based Retrieval for Software Troubleshooting
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...
متن کامل