Using Deep Reinforcement Learning for Exploratory Performance Testing of Software Systems With Multi-Dimensional Input Spaces-Reference-Cited by-同舟云学术

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Using Deep Reinforcement Learning for Exploratory Performance Testing of Software Systems With Multi-Dimensional Input Spaces

Published:2020 Issue: Volume:8 Page:195000-195020
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ahmad Tanwir^ORCID,Ashraf Adnan^ORCID,Truscan Dragos^ORCID,Domi Andi^ORCID,Porres Ivan^ORCID

Funder

Electronic Component Systems for European Leadership Joint Undertaking

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09239930.pdf?arnumber=9239930

Cited by 8 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. Survey on identification and prediction of security threats using various deep learning models on software testing;Multimedia Tools and Applications;2024-02-03

2. The role of Reinforcement Learning in software testing;Information and Software Technology;2023-12

3. Exploiting deep reinforcement learning and metamorphic testing to automatically test virtual reality applications;Software Testing, Verification and Reliability;2023-09-19

4. Automating Endurance Test for Flash-based Storage Devices in Samsung Electronics;2023 IEEE Conference on Software Testing, Verification and Validation (ICST);2023-04

5. Machine/Deep Learning for Software Engineering: A Systematic Literature Review;IEEE Transactions on Software Engineering;2023-03-01

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