Article in Journal ()
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.
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.
Binary similarity measure; Binary features; Combination of measures; Software modularization
|Authors||Naseem Rashid, Deris Mustafa Bin Mat, Maqbool Onaiza, Li Jingpeng, Shahzad Sarah, Shah Habib|
|Publication date online||22/09/2017|
|Date accepted by journal||12/04/2016|
Frontiers of Information Technology and Electronic Engineering: Volume 18, Issue 8