• Zhu, Qianqian. The application perspective of mutation testing. PhD dissertation. Delft University of Technology, Netherlands, 2020. [pdf]

  • Qianqian Zhu, Andy Zaidman, Annibale Panichella. How to kill them all: An exploratory study on the impact of code observability on mutation testing. Journal of Systems and Software,Volume 173, 2021, 110864, ISSN 0164-1212. https://doi.org/10.1016/j.jss.2020.110864.

  • Zhu, Qianqian, and Andy Zaidman. “Massively Parallel, Highly Efficient, but What About the Test Suite Quality? Applying Mutation Testing to GPU Programs.” 2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST). IEEE, 2020.
    [preprint pdf] [slides]

  • Zhu Q, Zaidman A, Panichella A. 2019. How to kill them all: an exploratory study on the impact of code observability on mutation testing. PeerJ Preprints 7:e27794v1 https://doi.org/10.7287/peerj.preprints.27794v1.
    [preprint pdf] [tool][slides]

  • Qianqian Zhu and Andy Zaidman, “Mutation Testing for Physical Computing,” The 18th IEEE International Conference on Software Quality, Reliability, and Security (QRS), Lisbon, Portugal, 2018
    [preprint pdf] [slides]

  • Qianqian Zhu, Annibale Panichella and Andy Zaidman, “An Investigation of Compression Techniques to Speed up Mutation Testing,” Proceedings of the 11th International Conference on Software Testing, Verification, and Validation (ICST), Västerås, Sweden, 2018.
    [pdf] [slides]

  • Qianqian Zhu, Annibale Panichella and Andy Zaidman, “Speeding-Up Mutation Testing via Data Compression and State Infection,” 2017 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), Tokyo, 2017, pp. 103-109. doi: 10.1109/ICSTW.2017.25
    [pdf] [slides]

  • Zhu Q, Panichella A, Zaidman A. A systematic literature review of how mutation testing supports quality assurance processes. Software Testing Verification Reliability 2018;28:e1675. https://doi.org/10.1002/stvr.1675
    [preprint pdf] [metadata]