|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|Peer Review Status:||Refereed|
Deris, Mustafa Bin Mat
|Title:||Improved Binary Similarity Measures for Software Modularization|
|Citation:||Naseem R, Deris MBM, Maqbool O, Li J, Shahzad S & Shah H (2017) Improved Binary Similarity Measures for Software Modularization. Frontiers of Information Technology and Electronic Engineering, 18 (8), pp. 1082-1107. https://doi.org/10.1631/FITEE.1500373|
|Abstract:||Various binary similarity measures have been employed in clustering approaches to make homogeneous groups of similar entities in the data. These similarity measures are mostly based only on the presence and absence of features. Binary similarity measures have also been explored with different clustering approaches (e.g., agglomerative hierarchical clustering) for software modularization to make the software systems understandable and manageable. Each similarity measure has its own strengths and weaknesses that result in improving and deteriorating the clustering results, respectively. This paper highlights the strengths of some well-known existing binary similarity measures for software modularization. Furthermore, based on these existing similarity measures, this paper introduces the improved new binary similarity measures. Proofs of the correctness with illustration and a series of experiments are presented to evaluate the effectiveness of our new binary similarity measures.|
|Status:||AM - Accepted Manuscript|
|Rights:||This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Publisher policy allows this work to be made available in this repository; Published in Frontiers of Information Technology & Electronic Engineering, August 2017, Volume 18, Issue 8, pp 1082–1107. The final publication is available at Springer via http://dx.doi.org/10.1631/FITEE.1500373|
|FITEE2016.pdf||Fulltext - Accepted Version||5.75 MB||Adobe PDF||View/Open|
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