• DocumentCode
    249157
  • Title

    Generation of high level views in reverse engineering using formal concept analysis

  • Author

    Nagendra Kumar, G. ; Aswani Kumar, Ch

  • Author_Institution
    Sch. of Inf. Technol. & Eng., VIT Univ., Vellore, India
  • fYear
    2014
  • fDate
    19-20 Aug. 2014
  • Firstpage
    334
  • Lastpage
    338
  • Abstract
    Object oriented systems are hard to comprehend because of different dependencies existing at different stages in the system. Inferring these dependencies among the components of object oriented systems is an essential requirement before performing any modifications in the system. So the maintenance of object oriented systems is a difficult process for software maintainers in software re-engineering. Here we present an approach for finding these dependencies by applying the conceptual clustering technique known as Formal Concept Analysis (FCA). In this paper, we show the results which are obtained by applying the approach. We generate the formal concepts and views at two different stages namely class and class hierarchy which shows different dependencies existed in the Java systems. Finally we present the experimental results of three Java applications on which we have tested our proposed approach.
  • Keywords
    Java; formal concept analysis; object-oriented programming; pattern clustering; reverse engineering; software engineering; FCA; Java applications; Java systems; conceptual clustering technique; formal concept analysis; object oriented systems; reverse engineering; software maintainers; software reengineering; Context; Formal concept analysis; Java; Lattices; Reverse engineering; Software; Software engineering; Formal Concept; Formal Concept Analysis; Formal Context; Object Oriented Systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networks & Soft Computing (ICNSC), 2014 First International Conference on
  • Conference_Location
    Guntur
  • Print_ISBN
    978-1-4799-3485-0
  • Type

    conf

  • DOI
    10.1109/CNSC.2014.6906678
  • Filename
    6906678