Usability feature selection via MBBAT: A novel approach

Citation data:

Journal of Computational Science, ISSN: 1877-7503, Vol: 23, Page: 195-203

Publication Year:
2017
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Citations 4
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DOI:
10.1016/j.jocs.2017.06.005
Author(s):
Deepak Gupta; Anil K. Ahlawat
Publisher(s):
Elsevier BV
Tags:
Mathematics; Computer Science
article description
In this paper, a metaheuristic algorithm has been introduced for software usability feature selection and evaluation. Usability is becoming one of the most significant aspects of quality of software. The term ‘usability’ has already been defined by the authors in their previous work in a reference to the hierarchical software usability model. This model combines various usability factors and features in a hierarchical manner. Here, we introduced MBBAT (Modified Binary Bat Algorithm) for usability feature selection to get an optimal solution for the search of useful usability features out of a given set of usability features. MBBAT is an extension of Binary Bat Algorithm(BBA) which is based on the bat's behavior and to the best of our knowledge, this algorithm is introduced for the first time in software engineering practices. The selected number of features and accuracy of proposed MBBAT algorithm is compared with the original BBA and the proposed metaheuristic algorithm outperforms the original BBA as it generates a fewer number of selected features and having low accuracy.