activity
20182021
most citedTime-aware Test Case Execution Scheduling for Cyber-Physical Systems

14 citations · 28 across the 4 of their papers we have counts for

collaborators

10 papers

cs.AI2021

Predictive Machine Learning of Objective Boundaries for Solving COPs

Helge Spieker, Arnaud Gotlieb

Solving Constraint Optimization Problems (COPs) can be dramatically simplified by boundary estimation, that is, providing tight boundaries of cost functions. By feeding a supervise…

cs.AI2021

Constraint-Guided Reinforcement Learning: Augmenting the Agent-Environment-Interaction

Helge Spieker

Reinforcement Learning (RL) agents have great successes in solving tasks with large observation and action spaces from limited feedback. Still, training the agents is data-intensiv…

cs.SE2020

A Fine-grained Data Set and Analysis of Tangling in Bug Fixing Commits

Steffen Herbold, Alexander Trautsch, Benjamin Ledel +45

Context: Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they actually study not only…

cs.SE20206 cited

Opening the Software Engineering Toolbox for the Assessment of Trustworthy AI

Mohit Kumar Ahuja, Mohamed-Bachir Belaid, Pierre Bernabé +7

Trustworthiness is a central requirement for the acceptance and success of human-centered artificial intelligence (AI). To deem an AI system as trustworthy, it is crucial to assess…

cs.SE2019

Adaptive Metamorphic Testing with Contextual Bandits

Helge Spieker, Arnaud Gotlieb

Metamorphic Testing is a software testing paradigm which aims at using necessary properties of a system-under-test, called metamorphic relations, to either check its expected outpu…

cs.SE201914 cited

Time-aware Test Case Execution Scheduling for Cyber-Physical Systems

Morten Mossige, Arnaud Gotlieb, Helge Spieker +2

Testing cyber-physical systems involves the execution of test cases on target-machines equipped with the latest release of a software control system. When testing industrial robots…