Using Machine Learning to Build Test Oracles: an Industrial Case Study on Elevators Dispatching Algorithms

Author:

Arrieta Aitor,Ayerdi Jon,Illarramendi Miren,Agirre Aitor,Sagardui Goiuria,Arratibel Maite

Publisher

IEEE

Cited by 15 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. Application of Quantum Extreme Learning Machines for QoS Prediction of Elevators’ Software in an Industrial Context;Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering;2024-07-10

2. Causal Test Adequacy;2024 IEEE Conference on Software Testing, Verification and Validation (ICST);2024-05-27

3. Search-Based Software Testing Driven by Automatically Generated and Manually Defined Fitness Functions;ACM Transactions on Software Engineering and Methodology;2023-12-23

4. Testing Causality in Scientific Modelling Software;ACM Transactions on Software Engineering and Methodology;2023-11-24

5. DevOps for Cyber-Physical Systems: Objectives, Results and Lessons Learned from the Adeptness H2020 Project;2023 26th Euromicro Conference on Digital System Design (DSD);2023-09-06

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