Challenges of Automated Software Testing with Robotic Process Automation RPA - A Comparative Analysis of UiPath and Automation Anywhere

  • Andrade D
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Abstract

The research work in this study explored the topic of Robotic Process Automation (RPA) and how it is being applied to modern software testing. Comparative analysis was designed to discover the features available from two of the leading RPA companies, UiPath and Automation Anywhere. The purpose of this study was to examine modern software testing challenges, utilization of RPA, and how RPA is being applied to solve significant challenges that cannot be addressed by manual software testing. RPA can heavily automate human tasks by emulating the same steps that a human would take, mostly in the form of UI interactions, but also in software scripts that emulate the process or tasks within a workflow commonly referred to as "bots" or "robots" [1]. Repetitive tasks automated with bots save money and increase the longevity of support by automating the tasks and generating quicker results than a human software tester. Implementing RPA into an organization adds value to business software management, performance, and processes of any complexity. Highlights of this study discussed strengths and weaknesses of RPA from the features available in both UiPath and Automation Anywhere when being applied to specific software testing challenges. The analysis of the information being collected for this research project mentioned authors' opinions, case studies, indicators, and other comprehensive applications. Comparisons being made included pros and cons, cost savings, and effective decision making when selecting automation. Future research needs to be conducted into improving RPA software testing of business logic with Artificial Intelligence (AI) and Machine Learning (ML).

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APA

Andrade, D. (2020). Challenges of Automated Software Testing with Robotic Process Automation RPA - A Comparative Analysis of UiPath and Automation Anywhere. International Journal of Intelligent Computing Research, 11(1), 1066–1072. https://doi.org/10.20533/ijicr.2042.4655.2020.0129

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