This paper proposes a methodology to generate artificial data sets to evaluate the behavior of machine learning techniques. The methodology relies in the definition of a domain an...
Joaquin Rios-Boutin, Albert Orriols-Puig, Josep Ma...
Software testing and software fault tolerance are two major techniques for developing reliable software systems, yet limited empirical data are available in the literature to eval...
Michael R. Lyu, Zubin Huang, Sam K. S. Sze, Xia Ca...
Recent advances in mechanical techniques for systematic testing have increased our ability to automatically find subtle bugs, and hence to deploy more dependable software. This pap...
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...
We consider the problems arising from using sequences of experiments to discover the causal structure among a set of variables, none of whom are known ahead of time to be an "...