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Boosting input data sequences generation for testing EFSM-specified systems using deep reinforcement learning

  • Published:2023-03 Issue: Volume:155 Page:107114
  • ISSN:0950-5849
  • Container-title:Information and Software Technology
  • language:en
  • Short-container-title:Information and Software Technology

Author:

Shu TingORCID,Wu CuipingORCID,Ding Zuohua

Funder

Natural Science Foundation of Zhejiang Province

Science and Technology Program of Zhejiang Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Computer Science Applications,Information Systems,Software

Reference41 articles.

1. A taxonomy of model-based testing approaches;Utting;Softw. Test. Verif. Reliab.,2012

2. A method enabling feasible conformance test sequence generation for EFSM models;Duale;IEEE Trans. Comput.,2004

3. EFSM-based test case generation: Sequence, data, and oracle;Yang;Int. J. Softw. Eng. Knowl. Eng.,2015

4. Confirming configurations in EFSM testing;Petrenko;IEEE Trans. Softw. Eng.,2004

5. Validation of SDL specifications using EFSM-based test generation;Wong;Inf. Softw. Technol.,2009

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Model-based diversity-driven learn-to-rank test case prioritization;Expert Systems with Applications;2024-12

2. A Parsing-Based Approach for Constructing Executable EFSM;2023 9th International Symposium on System Security, Safety, and Reliability (ISSSR);2023-06

3. The integration of machine learning into automated test generation: A systematic mapping study;Software Testing, Verification and Reliability;2023-05-02
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