SiDiTeR: Similarity Discovering Techniques for Robotic Process Automation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24310%2F23%3A00011256" target="_blank" >RIV/46747885:24310/23:00011256 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-031-43433-4_7" target="_blank" >https://doi.org/10.1007/978-3-031-43433-4_7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-43433-4_7" target="_blank" >10.1007/978-3-031-43433-4_7</a>

Jazyk výsledku

angličtina

Název v původním jazyce

SiDiTeR: Similarity Discovering Techniques for Robotic Process Automation

Popis výsledku v původním jazyce

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 RPA automations 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 aviable solution for mitigating the maintenance burden associated with RPA. This underscores the significance of process similarity in the RPA domain.

Název v anglickém jazyce

SiDiTeR: Similarity Discovering Techniques for Robotic Process Automation

Popis výsledku anglicky

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 RPA automations 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 aviable solution for mitigating the maintenance burden associated with RPA. This underscores the significance of process similarity in the RPA domain.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Lecture Notes in Business Information Processing

ISBN

—

ISSN

1865-1348

e-ISSN

—

Počet stran výsledku

14

Strana od-do

106-119

Název nakladatele

Springer Nature Switzerland

Místo vydání

—

Místo konání akce

Utrecht

Datum konání akce

1. 1. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001278532800007