English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Object oriented software with low cohesive classes can increase maintenancecost. Low cohesive classes are likely to be introduced into the software duringinitial design due to deviation from design principles and during evolution dueto software deterioration. Low cohesive class performs operations that shouldbe done by two or more classes. The low cohesive classes need to be identifiedand refactored using extract class refactoring to improve the cohesion. In thisregard, two aspects are involved; the first one is to identify the low cohesiveclasses and the second one is to identify the clusters of concepts in the lowcohesive classes for extract class refactoring. In this paper, we proposemetrics supplemented agglomerative clustering technique for covering the abovetwo aspects. The proposed metrics are validated using Weyuker's properties. Theapproach is applied successfully on two examples and on a case study.

Identifying Clusters of Concepts in a Low Cohesive Class for Extract Class Refactoring Using Metrics Supplemented Agglomerative Clustering Technique