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Cognitive Complexity Applied to Software Development: An Automated Procedure to Reduce the Comprehension Effort

Journal of ICT Research and Applications (JICTRA) · Vol. 16 No. 3 (2022) · pp. 281–299

DOI
10.5614/itbj.ict.res.appl.2022.16.3.6
ISSN
2338-5499, 2337-5787
Published
2022-12-31
Publisher
DRI - ITB
Language
eng

Abstract

The cognitive complexity of a software application determines the amount of human effort required to comprehend its internal logic, which results in a subjective measurement. The quantification process of the cognitive complexity as a metric is problematic since the factors representing the computation do not represent the exact human cognition. Therefore, the determination of cognitive complexity requires expansion beyond its quantification. The human comprehension effort related with a software application is associated with each phase of its development process. Correct requirements identification and accurate logical diagram generation prior to code implementation can lead to proper logical identification of software applications. Moreover, human comprehension is essential for software maintenance. Defect identification, correction and handling of code quality issues cannot be maintained without good comprehension. Therefore, cognitive complexity can be effectively applied to demonstrate human understandability inside the respective phases of requirements analysis, design, defect tracking, and code quality optimization. This study involved automation of the above-mentioned phases to reduce the manual human cognitive load and reduce cognitive complexity. It was found that the proposed system could enhance the average accuracy of requirements analysis and class diagram generation by 14.44% and 9.89% average accuracy incrementation through defect tracking and code quality issues compared to manual procedures.

Keywords

Collaboration network of the authors

2 authors · 1 co-authorship link · 1 across different organisations

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  • Sri Lanka Institute of Information Technology
  • University of Colombo
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journals.itb.ac.id/index.php/jictra/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Cognitive Complexity Applied to Software Development: An Automated Procedure to Reduce the Comprehension Effort</dc:title>
	<dc:creator>Wijendra, Dinuka R.</dc:creator>
	<dc:creator>Hewagamage, K. P.</dc:creator>
	<dc:subject xml:lang="en-US">cognitive complexity</dc:subject>
	<dc:subject xml:lang="en-US">cognitive load</dc:subject>
	<dc:subject xml:lang="en-US">comprehension</dc:subject>
	<dc:subject xml:lang="en-US">software development</dc:subject>
	<dc:subject xml:lang="en-US">subjectivity</dc:subject>
	<dc:description xml:lang="en-US">The cognitive complexity of a software application determines the amount of human effort required to comprehend its internal logic, which results in a subjective measurement. The quantification process of the cognitive complexity as a metric is problematic since the factors representing the computation do not represent the exact human cognition. Therefore, the determination of cognitive complexity requires expansion beyond its quantification. The human comprehension effort related with a software application is associated with each phase of its development process. Correct requirements identification and accurate logical diagram generation prior to code implementation can lead to proper logical identification of software applications. Moreover, human comprehension is essential for software maintenance. Defect identification, correction and handling of code quality issues cannot be maintained without good comprehension. Therefore, cognitive complexity can be effectively applied to demonstrate human understandability inside the respective phases of requirements analysis, design, defect tracking, and code quality optimization. This study involved automation of the above-mentioned phases to reduce the manual human cognitive load and reduce cognitive complexity. It was found that the proposed system could enhance the average accuracy of requirements analysis and class diagram generation by 14.44% and 9.89% average accuracy incrementation through defect tracking and code quality issues compared to manual procedures.</dc:description>
	<dc:publisher xml:lang="en-US">DRI - ITB</dc:publisher>
	<dc:date>2022-12-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
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	<dc:identifier>https://journals.itb.ac.id/index.php/jictra/article/view/19111</dc:identifier>
	<dc:identifier>10.5614/itbj.ict.res.appl.2022.16.3.6</dc:identifier>
	<dc:source xml:lang="en-US">Journal of ICT Research and Applications; Vol. 16 No. 3 (2022); 281-299</dc:source>
	<dc:source>2338-5499</dc:source>
	<dc:source>2337-5787</dc:source>
	<dc:source>10.5614/itbj.ict.res.appl.2022.16.3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/jictra/article/view/19111/6073</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 Journal of ICT Research and Applications</dc:rights>
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