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    Software refactoring at the package level using clustering techniques

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    Type
    Article
    Authors
    Alkhalid, Abdulaziz
    Alshayeb, M.
    Mahmoud, S. A.
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2011
    Permanent link to this record
    http://hdl.handle.net/10754/594111
    
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    Abstract
    Enhancing, modifying or adapting the software to new requirements increases the internal software complexity. Software with high level of internal complexity is difficult to maintain. Software refactoring reduces software complexity and hence decreases the maintenance effort. However, software refactoring becomes quite challenging task as the software evolves. The authors use clustering as a pattern recognition technique to assist in software refactoring activities at the package level. The approach presents a computer aided support for identifying ill-structured packages and provides suggestions for software designer to balance between intra-package cohesion and inter-package coupling. A comparative study is conducted applying three different clustering techniques on different software systems. In addition, the application of refactoring at the package level using an adaptive k-nearest neighbour (A-KNN) algorithm is introduced. The authors compared A-KNN technique with the other clustering techniques (viz. single linkage algorithm, complete linkage algorithm and weighted pair-group method using arithmetic averages). The new technique shows competitive performance with lower computational complexity. © 2011 The Institution of Engineering and Technology.
    Citation
    OCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"><html> <head> <title>Current Links for doi: 10.1049/iet-sen.2010.0070</title> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><link rel="stylesheet" rev="stylesheet" type="text/css" href="/docs/iPage/css/iet_body.css"> </head> <body bgcolor="#FFFFFF"> <table width="57%"> <tr> <td><a href="http://www.theiet.org"><img src="/docs/iPage/images/iet.gif" alt="Institution of Engineering and Technology" border="0" align="left"></a></td></tr> <tr> <td><br/></td> </tr> <tr> <td>The IET is a world leading professional organisation sharing and advancing knowledge to promote science, engineering and technology across the world. <br> <hr> </td> </tr> </table> <table width="57%"> <tr> <td><tr><td><b>Software refactoring at the package level using clustering techniques</b></td></tr><tr><td>Alkhalid,A. et al.</td></tr><tr><td><i>IET Software</i>(2011),5(3):274</td></tr><tr><td><a href='http://dx.doi.org/10.1049/iet-sen.2010.0070'>http://dx.doi.org/10.1049/iet-sen.2010.0070</td></tr></td> <tr> <tr><td><hr></td></tr> </table> <table width="57%"> <tr> <td colspan="2"> This article is available from multiple sources. <b>Please click on the logo</b> of the service to which you have a subscription, or click any logo to obtain pay-per-view access.<br><br></td> </tr> <tr> <td width="35%"><a href="http://digital-library.theiet.org/content/journals/10.1049/iet-sen.2010.0070"><img src="/docs/iPage/images/idl.gif" border="0" alt="IET Digital Library on Scitation"></a></td> <td width="65%"><br>&nbsp;&nbsp;Access the IET Digital Library<br><br></td> </tr> <tr> <td><br/><br/></td> </tr> <tr> <td><a href="http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5871781"><img src="/docs/iPage/images/iel.gif" border="0" alt="IEL on IEEE Xplore"></a></td> <td><br>&nbsp;&nbsp;Access the IEL (IEEE/IET Electronic Library) on IEEE Xplore&#174;</a><br><br></td></td> </tr> </table> </body></html>
    Sponsors
    The authors acknowledge the support of King Fahd University of Petroleum and Minerals in the development of this work. We also thank Dr. Sajjad Mahmoud and Mr. Irfan Ahmed for providing their expert evaluation of the approach.
    Publisher
    Institution of Engineering and Technology (IET)
    Journal
    IET Software
    DOI
    10.1049/iet-sen.2010.0070
    ae974a485f413a2113503eed53cd6c53
    10.1049/iet-sen.2010.0070
    Scopus Count
    Collections
    Articles; Computer Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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