1 citations · 1 across the 4 of their papers we have counts for
4 papers
DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators
Mahdi Taheri, Mohammad Riazati, Mohammad Hasan Ahmadilivani +5
While the role of Deep Neural Networks (DNNs) in a wide range of safety-critical applications is expanding, emerging DNNs experience massive growth in terms of computation power. I…
Machine Learning Testing in an ADAS Case Study Using Simulation-Integrated Bio-Inspired Search-Based Testing
Mahshid Helali Moghadam, Markus Borg, Mehrdad Saadatmand +3
This paper presents an extended version of Deeper, a search-based simulation-integrated test solution that generates failure-revealing test scenarios for testing a deep neural netw…
Performance Testing Using a Smart Reinforcement Learning-Driven Test Agent
Mahshid Helali Moghadam, Golrokh Hamidi, Markus Borg +4
Performance testing with the aim of generating an efficient and effective workload to identify performance issues is challenging. Many of the automated approaches mainly rely on an…
An Autonomous Performance Testing Framework using Self-Adaptive Fuzzy Reinforcement Learning
Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg +2
Test automation brings the potential to reduce costs and human effort, but several aspects of software testing remain challenging to automate. One such example is automated perform…