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10.5120/ijca2021921851 |
Dilshan I DeSilva, Saluka R Kodituwakku and Amalka J Pinidiyaarachchi. An Analytical Study of Cognitive Code-Level Object-Oriented Complexity Measures. International Journal of Computer Applications 183(45):8-14, December 2021. BibTeX
@article{10.5120/ijca2021921851, author = {Dilshan I. DeSilva and Saluka R. Kodituwakku and Amalka J. Pinidiyaarachchi}, title = {An Analytical Study of Cognitive Code-Level Object-Oriented Complexity Measures}, journal = {International Journal of Computer Applications}, issue_date = {December 2021}, volume = {183}, number = {45}, month = {Dec}, year = {2021}, issn = {0975-8887}, pages = {8-14}, numpages = {7}, url = {http://www.ijcaonline.org/archives/volume183/number45/32233-2021921851}, doi = {10.5120/ijca2021921851}, publisher = {Foundation of Computer Science (FCS), NY, USA}, address = {New York, USA} }
Abstract
Although several surveys on complexity measures proposed for the object-oriented approach can be found in the literature, a survey specific to cognitive code-level object-oriented complexity measures is yet to be published. Thus, a survey was conducted to make the reader aware of the cognitive code-level object-oriented complexity measures proposed since inception. Along with their calculations, the paper presents the existing cognitive code-level complexity measures in chronological order.In addition, it classifies the cognitive code-level measures based on the techniques adopted to test the validity, program component in which complexity is derived, adopted factors, the metrics used to ascertain the complexity created by each factor, capability to report program complexity as a combined value of all the considered factors, and how the program complexity value is expressed. Furthermore, the article presents the key findings uncovered from the survey and areas for development.
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Keywords
Software complexity, cognitive complexity, object-oriented approach, cognitive code-level complexity measures, survey