Research direction: Software Engineering


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I am a professor in Department of Computer Science, College of Information Science and Technology at Beijing University of Chemical Techology.

I hold a PhD degree in Computer Science from King's College London, supervised by Mark Harman and Nicolas Gold.

My research interests are software testing in combination with search-based techniques, source code analysis, program slicing and state based model slicing and testing. I orgnized the Chinese Search bases Software Engineering workshops (csbse.orgsince 2011.

Visit my profiles at GoogleDBLP and ORCID

I serve  IEEE SCAM working conference as Steering Committee member since 2017.


Work Experience

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Social Activities


  • * Search-based Software Engineering and Testing

    My present work on software engineering includes regression, test case prioritisation, test case generation using genetic, algorithms and empirical investigations of software.

  • * Program Slicing and Merging

    My present work on program slicing concentrates on empirical; studies of new slice-base analyzes and on generating a better; technique by combining program slicing and domain level techniques.

  • * State-based Model Slicing and Testing

    My interest in State-based Model Slicing and Testing has focused on developing algorithms, methods and techniques for scaling down the size and complexity of a model on both theoretical level and empirical level.


I am teaching Advanced Software Engineering during 2022-2023. 



Test Case Optimization in Continuous Integration based on Deep Reinforcement Learning

2019-01 to 2022-12 | Grant
National Natural Science Foundation of China
GRANT_NUMBER: 61872026

EFSM Slicing and Testing

2015-01 to 2018-12 | Grant
National Natural Science Foundation of China
GRANT_NUMBER: 61472025

GPGPU Based Test Case Prioritization

2012-01 to 2014-12 | Grant
National Natural Science Foundation of China
GRANT_NUMBER: 61170082

Test Generation Based on EFSM Slicing

2010-01 to 2011-12 | Grant
National Natural Science Foundation of China
GRANT_NUMBER: 60903002

Vertical Project

Horizontal Project


  • 2022

    An Empirical Study on Higher-Order Mutation-Based Fault Localization. Int. J. Softw. Eng. Knowl. Eng. 32(1): 1-35 ()
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    User behavior pattern mining and reuse across similar Android apps. J. Syst. Softw. 183111085 ()
  • :
    Theoretical Analysis and Empirical Study on the Impact of Coincidental Correct Test Cases in Multiple Fault Localization. IEEE Trans. Reliab. 71(2): 830-849 ()
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    Can Higher-Order Mutants Improve the Performance of Mutation-Based Fault Localization? IEEE Trans. Reliab. 71(2): 1157-1173 ()



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