Qunying Song

Orcid: 0000-0002-8653-0250

According to our database1, Qunying Song authored at least 13 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Industry Practices for Challenging Autonomous Driving Systems with Critical Scenarios.
ACM Trans. Softw. Eng. Methodol., May, 2024

NLP-TestGen.
Dataset, January, 2024

Critical Scenario Identification for Testing of Realistic Autonomous Driving Systems.
PhD thesis, 2024

An Empirically Grounded Path Forward for Scenario-Based Testing of Autonomous Driving Systems.
Proceedings of the Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024

Generating Executable Test Scenarios from Autonomous Vehicle Disengagements using Natural Language Processing.
Proceedings of the 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, 2024

Threats to Validity in Software Engineering - hypocritical paper section or essential analysis?
Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, 2024

2023
Threats to validity in software engineering research: A critical reflection.
Inf. Softw. Technol., December, 2023

Critical scenario identification for realistic testing of autonomous driving systems.
Softw. Qual. J., June, 2023

Industry-academia collaboration for realism in software engineering research: Insights and recommendations.
Inf. Softw. Technol., April, 2023

2022
A Scenario Distribution Model for Effective and Efficient Testing of Autonomous Driving Systems.
Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, 2022

Exploring ML testing in practice: lessons learned from an interactive rapid review with axis communications.
Proceedings of the 1st International Conference on AI Engineering: Software Engineering for AI, 2022

2021
Concepts in Testing of Autonomous Systems: Academic Literature and Industry Practice.
Proceedings of the 1st IEEE/ACM Workshop on AI Engineering - Software Engineering for AI, 2021

An Industrial Workbench for Test Scenario Identification for Autonomous Driving Software.
Proceedings of the 2021 IEEE International Conference on Artificial Intelligence Testing, 2021


  Loading...