Qunying Song

Qunying Song

Postdoctoral reseacher at UCL

Publications

  1. Gupta, Rushali, Qunying Song, Matthias Wagner, Emelie Engström, Emma Söderberg, Markus Borg, and Per Runeson. “AI Alignment for Ethical Compliance and Risk Mitigation in Industrial Applications.” In International Conference on Product-Focused Software Process Improvement, pp. 20-35. 2025. [Link]
  2. Song, Qunying, Avner Bensoussan, and Mohammad Reza Mousavi. “Synthetic versus real: an analysis of critical scenarios for autonomous vehicle testing.” Automated Software Engineering 32, no. 2 (2025): 37. [Link]
  3. Lago, Patricia, Per Runeson, Qunying Song, and Roberto Verdecchia. “Threats to validity in software engineering–hypocritical paper section or essential analysis?.” In Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, pp. 314-324. 2024. [Link]
  4. Song, Qunying, Emelie Engström, and Per Runeson. “An empirically grounded path forward for scenario-based testing of autonomous driving systems.” In Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, pp. 232-243. 2024. [Link]
  5. Song, Qunying, Emelie Engström, and Per Runeson. “Industry practices for challenging autonomous driving systems with critical scenarios.” ACM Transactions on Software Engineering and Methodology 33, no. 4 (2024): 1-35. [Link]
  6. Song, Qunying, Rune Anderberg, Henrik Olsson, and Per Runeson. “Generating executable test scenarios from autonomous vehicle disengagements using natural language processing.” In Proceedings of the 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, pp. 98-104. 2024. [Link]
  7. Verdecchia, Roberto, Emelie Engström, Patricia Lago, Per Runeson, and Qunying Song. “Threats to validity in software engineering research: A critical reflection.” Information and Software Technology 164 (2023): 107329. [Link]
  8. Song, Qunying, Kaige Tan, Per Runeson, and Stefan Persson. “Critical scenario identification for realistic testing of autonomous driving systems.” Software Quality Journal 31, no. 2 (2023): 441-469. [Link]
  9. Song, Qunying, and Per Runeson. “Industry-academia collaboration for realism in software engineering research: Insights and recommendations.” Information and Software Technology 156 (2023): 107135. [Link]
  10. Song, Qunying, Per Runeson, and Stefan Persson. “A scenario distribution model for effective and efficient testing of autonomous driving systems.” In Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, pp. 1-8. 2022. [Link]
  11. Song, Qunying, Markus Borg, Emelie Engström, Håkan Ardö, and Sergio Rico. “Exploring ML testing in practice: Lessons learned from an interactive rapid review with axis communications.” In Proceedings of the 1st International Conference on AI Engineering: Software Engineering for AI, pp. 10-21. 2022. [Link]
  12. Song, Qunying, Kaige Tan, Per Runeson, and Stefan Persson. “An industrial workbench for test scenario identification for autonomous driving software.” In 2021 IEEE International Conference on Artificial Intelligence Testing (AITest), pp. 81-82. IEEE, 2021. [Link]
  13. Song, Qunying, Emelie Engström, and Per Runeson. “Concepts in testing of autonomous systems: Academic literature and industry practice.” In 2021 IEEE/ACM 1st Workshop on AI Engineering-Software Engineering for AI (WAIN), pp. 74-81. IEEE, 2021. [Link]