5 citations · 9 across the 4 of their papers we have counts for
5 papers
Testing and Learning Symbolic Finite State Machines
Wen-ling Huang, Jan Peleska
Symbolic finite state machines (SFSMs) describe input/output behaviour using guards and output assignments with possibly infinite data domains. We study deterministic and completel…
Scenario-based System Testing for Distributed Robotics Applications
Jan Peleska, Felix Brüning, Wen-Ling Huang +1
We present the SCenario Specification Language (SCSL) for automated generation and execution of system-level tests. SCSL targets complex distributed systems (e.g., collaborating au…
A Stochastic Approach to Classification Error Estimates in Convolutional Neural Networks
Jan Peleska, Felix Brüning, Mario Gleirscher +1
This technical report presents research results achieved in the field of verification of trained Convolutional Neural Network (CNN) used for image classification in safety-critical…
Complete Agent-driven Model-based System Testing for Autonomous Systems
Kerstin I. Eder, Wen-ling Huang, Jan Peleska
In this position paper, a novel approach to testing complex autonomous transportation systems (ATS) in the automotive, avionic, and railway domains is described. It is intended to…
Complete Requirements-based Testing with Finite State Machines
Wen-ling Huang, Jan Peleska
In this paper, new contributions to requirements-based testing with deterministic finite state machines are presented. Elementary requirements are specified as triples consisting o…