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Automatic Microservices Identification Across Structural Dependency

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Hybrid Intelligent Systems (HIS 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 420))

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Abstract

Microservices oriented architecture has become increasingly popular, especially with the rise in the use of resource-intensive applications. Indeed, companies are faced with challenges related to the performance of their services in terms of technical infrastructure cost and in terms of development, deployment and system maintenance.

However, microservices allow the company to react much more promptly to new requirements and therefore avoid an endless development process over several years. Identifying microservices that are cohesive, loosely coupled, and fine-grained nowadays is a major challenge for most organizations. To address this challenge, we have proposed in this paper a technique for identifying microservices which decomposes our system using clustering. To this end, we have used the business process as the system input and we have only taken into account the aspect of structural dependency.

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Author information

Authors and Affiliations

  1. National School for Computer Science, Manouba, Tunisia

    Malak Saidi

  2. University Lyon 1, Villeurbanne, France

    Djamal Benslimane

  3. VPNC Lab, University of Jendouba, Jendouba, Tunisia

    Anis Tissaoui

  4. ISAMM, University of Manouba, Manouba, Tunisia

    Sami Faiz

Authors
  1. Malak Saidi
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  2. Anis Tissaoui
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  3. Djamal Benslimane
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  4. Sami Faiz
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Corresponding author

Correspondence to Anis Tissaoui .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Campus Centre de Créteil, Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

  3. Department of Computer Science, Università degli Studi di Milano, Milan, Milano, Italy

    Vincenzo Piuri

  4. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  5. University of Bari, Bari, Italy

    Gabriella Casalino

  6. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo

  7. Ontario Tech University, Oshawa, ON, Canada

    Patrick Hung

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Saidi, M., Tissaoui, A., Benslimane, D., Faiz, S. (2022). Automatic Microservices Identification Across Structural Dependency. In: Abraham, A., et al. Hybrid Intelligent Systems. HIS 2021. Lecture Notes in Networks and Systems, vol 420. Springer, Cham. https://doi.org/10.1007/978-3-030-96305-7_36

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