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Wireless Sensor Network Fault Localization
MPhil Thesis Defence Title: "Wireless Sensor Network Fault Localization" By Mr. Mian Qin Abstract Wireless sensor network (WSN) is a widely used distributed system to sense and interact with the physical world. Like other applications, wireless sensor network applications can be plagued by a variety of software faults. These faults can be critical and costly in debugging and deployment of sensor networks. Furthermore, these WSN software faults are difficult to locate. Therefore, automatic fault localization before deployment can significantly reduce the cost of debugging and deployment of a sensor network system. In general, debugging is composed of five steps: finding failure-triggering test cases, simplification of failed test cases, fault localization, repairing and regression testing. In another dimension, faults can reside in application logic, driver of on-board device and networking. Among these dimensions, fault localization has been considered the most important step of debugging, and application logic is more complex and bug-prone. We therefore focus on the study of fault localization of the application logic faults. In this thesis, first, an overview of the thesis will be presented. Then, WSN applications and automatic fault localization techniques will be introduced. After that, based on the state-of-art fault localization technique Tarantula, an adapted algorithm has been proposed in order to increase its effectiveness. We also evaluated this algorithm by conducting controlled experiments. As a result, the effectiveness of Tarantula has been improved. Based on this algorithm, we have also built an infrastructure for before-deployment fault localization on sensor network programs. This infrastructure provides various functions for different WSN debugging tasks performed by both developers and researchers. Date: Tuesday, 23 December 2008 Time: 2:00p.m.-4:00p.m. Venue: Room 3501 Lifts 25-26 Committee Members: Dr. Shing-Chi Cheung (Supervisor) Prof. Lionel Ni (Chairperson) Prof. Vincent Shen **** ALL are Welcome ****