Peter Madzik | Searcharxiv

arXiv2024

Hiden Topics in Robotic Process Automation -- an Approach based on AI

Robotic Process Automation (RPA) has rapidly evolved into a widely recognized and influential software technology. Its growing relevance has sparked diverse research efforts across various disciplines. This study aims to map the scientific landscape of RPA by identifying key thematic areas, tracking their development over time, and assessing their academic impact. To achieve this, we apply an unsupervised machine learning technique Latent Dirichlet Allocation (LDA) to analyze the abstracts of over 2,000 scholarly articles. Our analysis reveals 100 distinct research topics, with 15 of the most prominent themes featured in a science map designed to support future exploration and understanding of RPA's expanding research frontier.

cs.CY↗

arXiv2023

SiDiTeR: Similarity Discovering Techniques for Robotic Process Automation

Robotic Process Automation (RPA) has gained widespread adoption in corporate organizations, streamlining work processes while also introducing additional maintenance tasks. Effective governance of RPA can be achieved through the reusability of RPA components. However, refactoring RPA processes poses challenges when dealing with larger development teams, outsourcing, and staff turnover. This research aims to explore the possibility of identifying similarities in RPA processes for refactoring. To address this issue, we have developed Similarity Discovering Techniques for RPA (SiDiTeR). SiDiTeR utilizes source code or process logs from RPAautomations to search for similar or identical parts within RPA processes. The techniques introduced are specifically tailored to the RPA domain. We have expanded the potential matches by introducing a dictionary feature which helps identify different activities that produce the same output, and this has led to improved results in the RPA domain. Through our analysis, we have discovered 655 matches across 156 processes, with the longest match spanning 163 occurrences in 15 processes. Process similarity within the RPA domain proves to be a viable solution for mitigating the maintenance burden associated with RPA. This underscores the significance of process similarity in the RPA domain.

cs.RO↗