Qunying Song

19 papers A* 1A 1B 2Journal 10Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
AI Act high-risk AI compliance challenge and industry impact: A multiple case study.
Inf. Softw. Technol.
Matthias Wagner, Qunying Song, Markus Borg, Emelie Engström, Michal Lysek
2025 B conf
AI Alignment for Ethical Compliance and Risk Mitigation in Industrial Applications.
PROFES
Rushali Gupta, Qunying Song, Matthias Wagner, Emelie Engström, Emma Söderberg, Markus Borg, Per Runeson
2025 J jnl
Generative AI for Testing of Autonomous Driving Systems: A Survey.
CoRR
Qunying Song, He Ye, Mark Harman, Federica Sarro
2025 J jnl
Synthetic versus real: an analysis of critical scenarios for autonomous vehicle testing.
Autom. Softw. Eng.
Qunying Song, Avner Bensoussan, Mohammad Reza Mousavi
2024 — conf
An Empirically Grounded Path Forward for Scenario-Based Testing of Autonomous Driving Systems.
SIGSOFT FSE Companion
Qunying Song, Emelie Engström, Per Runeson
2024 — —
Critical Scenario Identification for Testing of Realistic Autonomous Driving Systems.
Qunying Song
2024 — conf
Generating Executable Test Scenarios from Autonomous Vehicle Disengagements using Natural Language Processing.
SEAMS@ICSE
Qunying Song, Rune Anderberg, Henrik Olsson, Per Runeson
2024 J jnl
Industry Practices for Challenging Autonomous Driving Systems with Critical Scenarios.
ACM Trans. Softw. Eng. Methodol.
Qunying Song, Emelie Engström, Per Runeson
2024 A conf
Threats to Validity in Software Engineering - hypocritical paper section or essential analysis?
ESEM
Patricia Lago, Per Runeson, Qunying Song, Roberto Verdecchia
2023 J jnl
Critical scenario identification for realistic testing of autonomous driving systems.
Softw. Qual. J.
Qunying Song, Kaige Tan, Per Runeson, Stefan Persson
2023 J jnl
Industry Practices for Challenging Autonomous Driving Systems with Critical Scenarios.
CoRR
Qunying Song, Emelie Engström, Per Runeson
2023 J jnl
Industry-academia collaboration for realism in software engineering research: Insights and recommendations.
Inf. Softw. Technol.
Qunying Song, Per Runeson
2023 J jnl
Threats to validity in software engineering research: A critical reflection.
Inf. Softw. Technol.
Roberto Verdecchia, Emelie Engström, Patricia Lago, Per Runeson, Qunying Song
2022 A* conf
A Scenario Distribution Model for Effective and Efficient Testing of Autonomous Driving Systems.
ASE
Qunying Song, Per Runeson, Stefan Persson
2022 J jnl
Exploring ML testing in practice - Lessons learned from an interactive rapid review with Axis Communications.
CoRR
Qunying Song, Markus Borg, Emelie Engström, Håkan Ardö, Sergio Rico
2022 B conf
Exploring ML testing in practice: lessons learned from an interactive rapid review with axis communications.
CAIN
Qunying Song, Markus Borg, Emelie Engström, Håkan Ardö, Sergio Rico
2021 — conf
An Industrial Workbench for Test Scenario Identification for Autonomous Driving Software.
AITest
Qunying Song, Kaige Tan, Per Runeson, Stefan Persson
2021 — conf
Concepts in Testing of Autonomous Systems: Academic Literature and Industry Practice.
WAIN@ICSE
Qunying Song, Emelie Engström, Per Runeson
2021 J jnl
Concepts in Testing of Autonomous Systems: Academic Literature and Industry Practice.
CoRR
Qunying Song, Emelie Engström, Per Runeson