We present work on a tool environment for model-based testing with the Abstract State Machine Language (AsmL). Our environment supports semiautomatic parameter generation, call seq...
Michael Barnett, Wolfgang Grieskamp, Lev Nachmanso...
Background: Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks ...
Peter Meinicke, Maike Tech, Burkhard Morgenstern, ...
Testing embedded software systems on the control units of vehicles is a safety-relevant task, and developing the test suites for performing the tests on test benches is time-consu...
Non-stop and highly available applications need to be dynamically adapted to new conditions in their execution environment, to new user requirements or to some situations usually u...
We explore the problem of budgeted machine learning, in which the learning algorithm has free access to the training examples’ labels but has to pay for each attribute that is s...
Kun Deng, Chris Bourke, Stephen D. Scott, Julie Su...