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Using Process Mining to Leverage the Development of a Family of Mobile Applications

https://doi.org/10.15514/10.15514/ISPRAS-2023-35(3)-13

Abstract

Enterprises often provide their services via a family of applications based on various platforms. Applications in such a family can behave differently. Their development processes can differ as well. Moreover, modern development processes are often complex and sometimes vague. This can lead to bugs, defects, and unwanted discrepancies in applications. In this paper, we show that process mining can be applied to leverage the development in such a case. Real-life models can be discovered and investigated by the developer teams in order to reveal differences in application behaviour, find bugs, and highlight inefficiencies. We consider datasets with event data of two types. Firstly, we analyse event logs of Android and iOS applications of the same product family. Secondly, we consider event data from working repositories of these applications. We show how by analysing such datasets, the real-life development process can be discovered. Besides, application event logs can help to find more and less severe bugs and unwanted behaviour.

About the Authors

Lyudmila Alexandrovna REZUNIK
HSE University
Russian Federation

Bachelor of Software Engineering



Alisa Igorevna PEREVOZNIKOVA
HSE University
Russian Federation

Bachelor of Software Engineering



Daria Valerievna EREMINA
HSE University
Russian Federation

Bachelor of Software Engineering



Alexey Alexandrovich MITSYUK
HSE University
Russian Federation

PhD in Computer Science, Associate Professor, Senior Research Fellow at the Laboratory of Process-Aware Information Systems (PAIS Lab) of the Faculty of Computer Science at the HSE University.



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Review

For citations:


REZUNIK L.A., PEREVOZNIKOVA A.I., EREMINA D.V., MITSYUK A.A. Using Process Mining to Leverage the Development of a Family of Mobile Applications. Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2023;35(3):171-186. https://doi.org/10.15514/10.15514/ISPRAS-2023-35(3)-13



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ISSN 2079-8156 (Print)
ISSN 2220-6426 (Online)