Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/26942
Title: MiSAR:The MicroService Architecture Recovery Toolset
Authors: Ali, N
Alshuqayran, N
Faqeeh, R
Rohman, T
Solis, C
Keywords: microservice;architecture reconstruction;architecture recovery;architectural views;model driven engineering;model driven architecture
Issue Date: 30-Jul-2024
Publisher: Springer
Citation: Ali, N. et al. (2024) 'MiSAR:The MicroService Architecture Recovery Toolset', in: Tekinerdoğan, B., et al. (eds). Software Architecture. ECSA 2023 Tracks, Workshops, and Doctoral Symposium. ECSA 2023. Lecture Notes in Computer Science, vol 14590. Cham: Springer, pp. 326 - 341. doi: 10.1007/978-3-031-66326-0_20.
Series/Report no.: Lecture Notes in Computer Science;vol 14590
Abstract: This paper presents the MicroService Architecture Recovery (MiSAR) toolset for software engineers (software architects and developers) that need to semi-automatically obtain as-implemented architectural models of existing microservice-based systems. The MiSAR approach has been designed following Model Driven Architecture, and a set of components have been developed to support the semi-automatic support of MiSAR. The toolset first parses microservice-based systems and generates a Platform-Specific Model, which is an abstract representation of the system using the technology. Then, a model transformation engine automatically generates a Platform Independent Model which represents the as-implemented microservice architectural mode of a system. To support the visualization of as-implemented architectural models, the Graphical Model Generator component of the toolset can be used. The Graphical Model Generator allows the software engineer to obtain quantitative metrics of the microservice architectural model and UML diagrams representing different views of the architecture.
Description: Demonstrated on the Automation track on Wednesday 20 September 2023 (see: https://conf.researchr.org/program/ecsa-2023/program-ecsa-2023/?date=Wed%2020%20Sep%202023).
URI: https://bura.brunel.ac.uk/handle/2438/26942
DOI: https://doi.org/10.1007/978-3-031-66326-0_20
ISBN: 978-3-031-66325-3 (pbk)
978-3-031-66326-0 (ebk)
ISSN: 0302-9743
Other Identifiers: ORCiD: Nour Ali https://orcid.org/0000-0002-0161-5600
Appears in Collections:Dept of Computer Science Embargoed Research Papers

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