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�������պ����ѧѧ�� 2009, Vol. 35 Issue (10) :1201-1205    DOI:
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������1, ��ï��1, ����ϼ1, ��ѩ÷2*
1. �������պ����ѧ �����ѧԺ, ���� 100191;
2. ��������ѧԺ ���ѧ��, ���� 100083
BBN-based fault localization technique
Liu Yongpo1, Jin Maozhong1, Jia Xiaoxia1, Liu Xuemei2*
1. School of Computer Science and Technology, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
2. College of Software, Beijing City University, Beijing 100083, China

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ժҪ ���϶�λ��Ŀ���ǰ�������ԱѰ������ʧЧ��ԭ������λ��,�Լӿ���Թ���.���Ϻ�ʧЧ��Ĺ�ϵ�����dz�����,����ֱ���������ϵ�ʧЧ��ת��.�����˲��ò�������ķ���,������ڿ���ģʽ,������������Ҷ˹����,�ڵ��ɿ���ģʽ���䷽�������߹���;�����˱�Ҷ˹���繹���㷨,������ظ��ʵĶ��弰BBN(Bayesian Belief Network)�и����ߵ��������ʼ��㹫ʽ.���������㷨,�õ��������ϵ�ģ��,������õ�ÿ��ģ��������ϵĸ���.������۷���,��������ʵ����֤,ȡ����ƽ��0.761�Ķ�׼�ʺ�0.737�Ķ�ȫ��,��λ���������Ӧ�ü�ֵ.
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Abstract�� Fault localization techniques help programmers find out the locations and the causes of the faults and accelerate the debugging process. The relation between the fault and the failure is usually complicated, making it hard to deduce how a fault causes the failure. At present, analysis of variance is broadly used in many recent correlative researches. A Bayesian belief network(BBN) for fault reasoning was constructed based on the suspicious pattern, whose nodes consist of the suspicious pattern and the callers of the methods that constitute the suspicious pattern. The constructing algorithm of the BBN, the correlative probabilities, and the formula for the conditional probabilities of each arc of the BBN were defined. A reasoning algorithm based on the BBN was proposed, through which the faulty module can be found and the probability for each module containing the fault can be calculated. An evaluation method was proposed. Experiments were executed to evaluation the fault localization technique. The data demonstrated that 0.761 in accuracy and 0.737 in recall on average were achieved by this technique. It is very effective in fault localization and has high practical value.
Keywords�� fault location   differentiation   pattern recognition   probability     
Received 2008-10-21;
Fund:

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About author: ������(1971-),��,����������,��ʿ��,liuypo@sei.buaa.edu.cn.
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������, ��ï��, ����ϼ, ��ѩ÷.����BBN�Ĺ��϶�λ����[J]  �������պ����ѧѧ��, 2009,V35(10): 1201-1205
Liu Yongpo, Jin Maozhong, Jia Xiaoxia, Liu Xuemei.BBN-based fault localization technique[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2009,V35(10): 1201-1205
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