Robot Testing from a machine learning perspective
Vinod Yadav, Raphael Kwaku Botchway, Roman Šenkeřík, Zuzana Komínková Oplatková · 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET) · 2021
The need to scale software test automation while managing the test automation process within a reasonable time frame remains a crucial challenge for software development teams (DevOps). Unlike hardware, the software cannot wear out but can fail to satisfy the functional requirements it is supposed to meet due to the defects observed during system operation. In this era of big data, DevOps teams can deliver better and efficient code by utilizing machine learning (ML) to scan their new codes and identify test coverage gaps. This study introduces robot testing and machine learning to manage the test automation process to guarantee software reliability and quality within a reasonable timeframe.