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Dynamic Random Testing (DRT) is a testing strategy to improve traditional random testing and random-partition testing strategies. The essential idea of DRT is that the testing profile, based on which test classes are chosen to select next test case, should be dynamically adjusted according to the testing history. DRT can have various forms depending on parameters settings, application scenarios and...
Adaptive testing is the counterpart of adaptive control in software testing. It means that software testing strategy should be adjusted on-line by using the testing data collected during software testing as our understanding of the software under test improves. In doing so, online estimation of parameters plays a crucial role. In this paper, we investigate the computational complexity of the parameter...
In this paper we proposed a novel algorithm for image restoration and parameters estimation with a wavelet domain Student-t priors using variational Bayesian method. Because the conventional spatial domain hierarchical prior models have the shortcoming that normalization constant cannot found in closed form, we resort to wavelet domain prior model that avoid the above shortcoming. The restored image...
Adaptive software testing is the counterpart of adaptive control in software testing. It means that software testing strategy should be adjusted online by using the testing data collected during software testing as our understanding of the software under test improves. Previous studies on adaptive testing rely on a simplified Controlled Markov Chain (CMC) model for software testing which employs several...
In data stream management systems (DSMSs), request handling has to meet various QoS requirements. Traditional open-loop DSMS ignores system status information and run-time history in decision making and is unable to achieve stable QoS performance over run-time as the workload or environment changes. This paper discusses the design of a close-loop DSMS that applies adaptive control in control theory...
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