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A Method of Component Discovery in Cloud Migration

  • Jian-tao Zhou
  • Ting Wu
  • Yan Chen
  • Jun-feng ZhaoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11242)

Abstract

Cloud migration is an important means of software development on the cloud. The identification of reusable components of legacy systems directly determines the quality of cloud migration. The existed clustering algorithms do not consider the factor of relation types between classes, which affects the accuracy of clustering result. In this paper, the relation type information between classes is introduced in software clustering. Multi-objective genetic algorithm is used to cluster the module dependency graph with the relationship types (R-MDG). The experimental results show that the above method can effectively improve the quality of reusable components.

Keywords

Reusable component Software clustering Relation type Genetic algorithm 

Notes

Acknowledgment

The authors wish to thank Natural Science Foundation of China under Grant No. 61462066, 61662054, Natural Science Foundation of Inner Mongolia under Grand No. 2015MS0608, Inner Mongolia Science and Technology Innovation Team of Cloud Computing and Software Engineering and Inner Mongolia Application Technology Research and Development Funding Project “Mutual Creation Service Platform Research and Development Based on Service Optimizing and Operation Integrating”. Inner Mongolia Engineering Lab of Cloud Computing and Service Software and Inner Mongolia Engineering Lab of Big Data Analysis Technology.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Jian-tao Zhou
    • 1
  • Ting Wu
    • 1
  • Yan Chen
    • 1
  • Jun-feng Zhao
    • 1
    Email author
  1. 1.College of Computer ScienceInner Mongolia UniversityHohhotChina

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