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Debugging or fault localization is one of the most challenging tasks during software development. Many tools have been developed to reduce the amount of effort and time software developers have to spend on fault localization. In this paper, we evaluate the effectiveness of a fault localization tool called BEN in localizing different types of software fault. Assuming that combinatorial testing has...
Combinatorial testing (CT) aims at detecting interaction failures between parameters in a system. Identifying the failure-inducing combinations of a failing test configuration can help developers find the cause of this failure. However, most studies in CT focus on detecting the failures rather than identifying failure-inducing combinations. In this paper, we propose the notion of a tuple relationship...
Software fault diagnosis is a process of locating the source of faults based on the testing result (pass or fail) of each test case. It plays an important role in software debugging. However, because of the continuous expansion in software size and complexity, it becomes more and more difficult to diagnose software faults quickly and effectively. Combinatorial testing (CT) is a widely used black-box...
An online fan fault diagnosis system is proposed based on wavelet and neural network, and the system is implemented on the LabVIEW platform. Relying on the noise signal from the fan, the recognition system utilizes power spectrum gravity center, sound level, wavelet frequency segment power of the signal as feature vectors, and the BP network as classifier for fault diagnosis. The experimental results...
A Java monitor is a Java class that defines one or more synchronized methods. Unlike a regular object, a Java monitor object is intended to be accessed by multiple threads simultaneously. Thus, testing a Java monitor can be significantly different from testing a regular class. In this paper, we propose a state exploration-based approach to testing a Java monitor. A novel aspect of our approach is...
This paper introduces a new bearing fault detection and diagnosis scheme based on relevance vector machine (RVM) of vibration signals, i.e. two relevance vector machines are viewed as observer and classifier respectively. The observer is applied to identify and estimate various faults of bearing to gain fault state residual sequence while the classifier is used to classify multiple fault modes of...
Condition monitoring is very important in machinery engineering study. In most conditions, normal signals are acquired easily but fault samples are difficult to be gained. Because of lacking enough fault samples, the machine diagnosis meets difficulties. Support vector data description (SVDD) is a single classifier and it can distinguish the normal and fault condition just using normal samples. In...
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