Kerong Ben

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Crosscutting behaviors and features of architectural units have always been a tricky issue in software architecture design. If not well treated, they may lead to a number of architectural breakdowns, such as increased maintenance overhead, reduced reuse capability, and architectural erosion over the lifetime of a system. Unfortunately, traditional software(More)
It would be valuable to use metrics to identify the fault-proneness of software modules. However, few research works are on how to select appropriate metrics for fault-proneness prediction currently. We conduct a large-scale comparative experiment of nine different software metrics reduction methods over eleven public-domain data sets from the NASA metrics(More)
The existing Web services integration systems are facing three major problems: the structure of integration framework is inflexible and is difficult to adapt to the complex network circumstance; Web services lack autonomy, individuality and intelligence; Single mode of service integration is difficult to ensure the QoS of integration system. Around these(More)
Software systems are required to adapt themselves dynamically to the ever changing environment and requirements. Architectural reflection represents a principled means to address adaptively. In this paper, a framework of supporting software evolution based on architectural reflection is proposed. Architecture information is reified as explicit and(More)
A critical issue for software evolution on the fly is the adaptation of their runtime architecture. In fact, itpsilas hard to preserve service continuity and assure evolution process safety. To deal with this issue, we propose in this paper an approach to modify the runtime architecture indirectly thought meta-operators based on architectural reflection(More)
Lots of growing neural network models have been proposed to tackle the incremental learning problem, but they also bring about the problem of fast growing complex structure. In this paper, we present a combinational Neural Network of SOM (Self-Organizing Maps) and RBF (Radial Basis Function) based on incremental learning method. The experiment of acoustic(More)
With the rapid development of information technology, it is inevitable that the distributed mobile computing will evolve to pervasive computing gradually whose final goal is fusing the information space composed of computers with the physical space in which the people are working and living in. However, most of WSN contexts coming from may be more and more(More)
Based on SVM and incremental learning, this paper proposes a new method for recognition of underwater vehicle noise source on small samples. The new method may establish a classifier which structure is dynamic adjustable, and it can solve both Example- Incremental learning and Class-Incremental learning. The experimentation shows the generalization of(More)