Software Cognitive Information Measure based on Relation Between Structures

TL;DR

This paper introduces the Structured Cognitive Information Measure (SCIM), a new approach to quantifying software cognitive complexity based on the relation between structures and integrating granular computing, validated through theoretical properties.

Contribution

It proposes the Scope Information Complexity Number (SICN) and a cognitive complexity measure based on functional decomposition, extending existing complexity measures with theoretical validation.

Findings

The measure unifies complexity factors reflecting human cognition.

The approach is validated through nine Weyuker's properties.

It offers a new perspective on software complexity analysis.

Abstract

Cognitive complexity measures quantify human difficulty in understanding the source code based on cognitive informatics foundation. The discipline derives cognitive complexity on a basis of fundamental software factors i.e, inputs, outputs, and internal processing architecture. An approach to integrating Granular Computing into the new measure called Structured Cognitive Information Measure or SCIM. The proposed measure unifies and re-organizes complexity factors analogous to human cognitive process. However, according to the methodology of software and the scope of the variables, Information Complexity Number(ICN) of variables is depended on change of variable value and cognitive complexity is measured in several ways. In this paper, we define the Scope Information Complexity Number (SICN) and present the cognitive complexity based on functional decomposition of software, including theoretical validation through nine Weyuker's properties.