SiDiTeR: Similarity Discovering Techniques for Robotic Process Automation
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
SiDiTeR: Similarity Discovering Techniques for Robotic Process Automation
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Business Information Processing
ISBN
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ISSN
1865-1348
e-ISSN
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Number of pages
14
Pages from-to
106-119
Publisher name
Springer Nature Switzerland
Place of publication
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Event location
Utrecht
Event date
Jan 1, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001278532800007