Architecture Extraction for Message-Based Systems from Dynamic Analysis: Unterschied zwischen den Versionen

Aus SDQ-Institutsseminar
Keine Bearbeitungszusammenfassung
Keine Bearbeitungszusammenfassung
 
Zeile 5: Zeile 5:
|betreuer=Snigdha Singh
|betreuer=Snigdha Singh
|termin=Institutsseminar/2022-01-21
|termin=Institutsseminar/2022-01-21
|vortragsmodus=in Präsenz
|vortragsmodus=online
|kurzfassung=We try to extend the existing approach to support the architecture model extraction of
|kurzfassung=Distributed message-based microservice systems architecture has seen considerable evolution in recent years, making them easier to extend, reuse and manage. But, the challenge lies in the fact that such software systems are constituted of components that are more and more autonomous, distributed, and are deployed with different technologies. On the one hand such systems through their  flexible architecture provide a lot of advantages. On the other hand, they are more likely to be changed fast and thus make their architecture less reliable and up-to-date. Architecture reconstruction method can support to obtain the updated architecture at different phases of development life cycle for software systems. However, the existing architecture reconstruction methods do not support the extraction for message-based microservice systems. In our work we try to handle this problem by extending an existing approach of architecture model extraction of message-based microservice systems from their tracing data (source code instrumented) in a way that such systems can be supported. Through our approach, we provide a way to automatically extract performance models for message-based microservice systems through dynamic analysis. We then evaluate our approach with the comparison of extracted model with the manual model with statistical metrics such as precision, recall and F1-score in order to find out the accuracy of our extracted model.
microservice-based systems communicating via message-based methods. We build the model from dynamic analysis of from tracing data collected the source code instrumentation of the existing system.
}}
}}

Aktuelle Version vom 20. Januar 2022, 18:21 Uhr

Vortragende(r) Fatma Chebbi
Vortragstyp Bachelorarbeit
Betreuer(in) Snigdha Singh
Termin Fr 21. Januar 2022
Vortragsmodus online
Kurzfassung Distributed message-based microservice systems architecture has seen considerable evolution in recent years, making them easier to extend, reuse and manage. But, the challenge lies in the fact that such software systems are constituted of components that are more and more autonomous, distributed, and are deployed with different technologies. On the one hand such systems through their flexible architecture provide a lot of advantages. On the other hand, they are more likely to be changed fast and thus make their architecture less reliable and up-to-date. Architecture reconstruction method can support to obtain the updated architecture at different phases of development life cycle for software systems. However, the existing architecture reconstruction methods do not support the extraction for message-based microservice systems. In our work we try to handle this problem by extending an existing approach of architecture model extraction of message-based microservice systems from their tracing data (source code instrumented) in a way that such systems can be supported. Through our approach, we provide a way to automatically extract performance models for message-based microservice systems through dynamic analysis. We then evaluate our approach with the comparison of extracted model with the manual model with statistical metrics such as precision, recall and F1-score in order to find out the accuracy of our extracted model.