Abstract
Due to recent changes and advancements in software sector, there was an alarming need to cut down time as well as efforts required during complete software development process. While constructing and designing product and services, assuring the quality of software product is very important aspect in order to boost market value of that product. To attain both quality as well as productivity objectives, there is an urge for software reusability. Reusability is an essential measure that can be used to improve overall software quality with lesser cost and efforts. Data Mining is a process to extract useful data from a larger set containing raw data. It also means analyzing patterns from large collection of data. In Object-Oriented (O–O) Software Systems, class reusability can be easily obtained by inspecting metrics values. Inspecting metric values would save time to develop software components from initial phase. In this paper various software metrics related to software reusability of Object-oriented (O–O) software systems has been outlined with the help of MATLAB environment. SOM Technique was applied to create clusters of metrics values that were derived from two Java based system that were a part of COMET dataset that was easily available online. The goal of this study was to identify relationship among metrics values and different level of reusability of particular class. This study shows how SOM technique can be applied on metrics with SOM grids of different sizes. The study depicts elimination of two of the software metrics i.e. NOC and DIT due to poor distribution depicted by both of them.
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Acknowledgements
I would like to acknowledge Dr Parul Gandhi, Professor and Ph.D. Coordinator in Faculty of Computer Applications, MRIIRS, Faridabad for her continuous support and helpful guidance during the preparation time of this article.
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Bisht, B., Gandhi, P. (2022). Reusability Estimation of Object-Oriented (O–O) Systems Using SOM Technique. In: Singh, P.K., Kolekar, M.H., Tanwar, S., Wierzchoń, S.T., Bhatnagar, R.K. (eds) Emerging Technologies for Computing, Communication and Smart Cities. Lecture Notes in Electrical Engineering, vol 875. Springer, Singapore. https://doi.org/10.1007/978-981-19-0284-0_40
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