• DocumentCode
    76091
  • Title

    An orthogonal approach to reusable component discovery in cloud migration

  • Author

    Zhao Junfeng ; Zhou Jiantao ; Yang Hongji ; Liu Guoping

  • Author_Institution
    Inner Mongolia Univ., Hohhot, China
  • Volume
    12
  • Issue
    5
  • fYear
    2015
  • fDate
    May-15
  • Firstpage
    134
  • Lastpage
    151
  • Abstract
    As an innovative software application mode, Software as a service (SaaS) shows many attractive advantages. Migrating legacy system to SaaS can make outdated systems revived. In the process of migration, the existing valuable components need to be discovered and reused in order that the target system could be developed/integrated more efficiently. An innovative approach is proposed in this paper to extract the reusable components from legacy systems. Firstly, implementation models of legacy system are recovered through reverse engineering. Secondly, function models are derived by vertical clustering, and then logical components are discovered by horizontal clustering based on the function models. Finally, the reusable components with specific feature descriptions are extracted. Through experimental verification, the approach is considered to be efficient in reusable component discovery and to be helpful to migrating legacy system to SaaS.
  • Keywords
    cloud computing; pattern clustering; software maintenance; software reusability; SaaS; cloud migration; experimental verification; function models; horizontal clustering; innovative software application mode; legacy system; logical components; orthogonal approach; reusable component discovery; reverse engineering; software as a service; vertical clustering; Aging; Algorithm design and analysis; Clustering algorithms; Computer architecture; Software algorithms; Software as a service; architecture recovery; horizontal clustering; legacy system; reusable component; vertical clustering;
  • fLanguage
    English
  • Journal_Title
    Communications, China
  • Publisher
    ieee
  • ISSN
    1673-5447
  • Type

    jour

  • DOI
    10.1109/CC.2015.7112036
  • Filename
    7112036