TCM: Test Coverage Metrics For Artificial Intelligence

Description: This project studies the adaptation of software engineering techniques -- in particular, coverage-guided testing -- to work with machine/deep learning.

Funding Agency: Defence Science and Technology Laboratory (Dstl)

Project Time: 2018 - 2021

  • Xiaowei Huang (PI)
  • Sven Schewe (Co-I)
  • Simon Maskell (Co-I)
  • Youcheng Sun (postdoc, 2018-2019, placed at Oxford)
  • Nicolas Berthier (postdoc, 2019-)
External Collaborators
  • Daniel Kroening (Co-I, Oxford, 2018-2019)
  • Wenjie Ruan (Co-I, Lancaster, 2019-2021)
  • Youcheng Sun (Co-I, QUB, 2019-2021)
  • Jie Meng (Co-I, Loughborough, 2019-2021)
  • Concolic testing for deep neural networks.
    • Youcheng Sun, Min Wu, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska, and Daniel Kroening.
    • In Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering (ASE 2018). Association for Computing Machinery, New York, NY, USA, 109–119.
    • DOI:
  • Feature-Guided Black-Box Safety Testing of Deep Neural Networks.
    • Matthew Wicker, Xiaowei Huang, Marta Kwiatkowska.
    • TACAS 2018.
  • Reachability Analysis of Deep Neural Networks with Provable Guarantees.
    • Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska.
    • IJCAI 2018.
  • Structural Test Coverage Criteria for Deep Neural Networks.
    • Youcheng Sun, Xiaowei Huang, Daniel Kroening, James Sharp, Matthew Hill, and Rob Ashmore.
    • ACM Trans. Embed. Comput. Syst. 18, 5s, Article 94 (October 2019), 23 pages.
    • DOI:
  • Towards Integrating Formal Verification of Autonomous Robots with Battery Prognostics and Health Management.
    • Xingyu Zhao, Matt Osborne, Jenny Lantair, Valentin Robu, David Flynn, Xiaowei Huang, Michael Fisher, Fabio Papacchini, Angelo Ferrando.
    • SEFM2019.
  • Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the Hamming Distance.
    • Wenjie Ruan, Min Wu, Youcheng Sun, Xiaowei Huang, Daniel Kroening, Marta Kwiatkowska.
    • IJCAI 2019.
  • Gaze-based Intention Anticipation over Driving Manoeuvres in Semi-Autonomous Vehicles.
    • Min Wu, Tyron Louw, Morteza Lahijanian, Wenjie Ruan, Xiaowei Huang, Natasha Merat, Marta Kwiatkowska.
    • 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, 2019, pp. 6210-6216.
    • doi: 10.1109/IROS40897.2019.8967779
  • A game-based approximate verification of deep neural networks with provable guarantees.
    • Min Wu, Matthew Wicker, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska.
    • Theoretical Computer Science Volume 807, 6 February 2020, Pages 298-329.
  • A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability.
    • Xiaowei Huang, Daniel Kroening, Wenjie Ruan, James Sharp, Youcheng Sun, Emese Thamo, Min Wu, Xinping Yi.
    • Computer Science Review, Volume 37, 2020, 100270, ISSN 1574-0137.
  • DeepConcolic: Testing and Debugging Deep Neural Networks.
    • Y. Sun, X. Huang, D. Kroening, J. Sharp, M. Hill and R. Ashmore.
    • 2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), Montreal, QC, Canada, 2019, pp. 111-114.
    • doi: 10.1109/ICSE-Companion.2019.00051
  • A Safety Framework for Critical Systems Utilising Deep Neural Networks.
    • Xingyu Zhao, Alec Banks, James Sharp, Valentin Robu, David Flynn, Michael Fisher, Xiaowei Huang
    • SAFECOMP 2020.
  • Reliability Validation of Learning Enabled Vehicle Tracking.
    • Y. Sun, Y. Zhou, S. Maskell, J. Sharp and X. Huang
    • 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020, pp. 9390-9396.
    • doi: 10.1109/ICRA40945.2020.9196932
  • Practical Verification of Neural Network Enabled State Estimation System for Robotics.
    • W. Huang, Y. Zhou, Y. Sun, S. Maskell, J. Sharp and X. Huang
    • IROS 2020.

Please feel free to contact me for more information.