Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...
Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen...
We show how model checking and symbolic execution can be used to generate test inputs to achieve structural coverage of code that manipulates complex data structures. We focus on ...
Willem Visser, Corina S. Pasareanu, Sarfraz Khursh...
This paper proposes a stochastic voting for testing a large number of Web Services (WS) under group testing. In the future, a large number of WS will be available and they need to...
Wei-Tek Tsai, Dawei Zhang, Raymond A. Paul, Yinong...
Modularity is one of the most important properties of a software design, with significant impact on changeability and evolvability. However, a formalized and automated approach i...