Jul 24, 2018 · In this paper, information entropy and its application towards measuring software complexity are explored, along with the formulation of an information entropy ...
Apr 28, 2024 · The base concept of the entropy calculation proposed by Shannon measures how much information is produced by a system or how much uncertainty ...
To broaden the application of the proposed metric, the execution times of nodes in the control flow graphs are also incorporated. Further, the metric is ...
ABSTRACT: A review of the existing work on software complexity metrics shows the use of McCabe's cyclomatic number, Halstead's software science, the number of ...
The formulation of an information entropy based complexity measure that considers logical decision-making, processes, and software statement interaction ...
The concept Entropy in terms of information theory is seen as the average amount of information or the rate of information produced when forming a message, ...
Information entropy applied to software based control flow graphs. Aditya Akundi, Eric Smith, Tzu-Liang Tseng · Details · Contributors · Fields of science ...
In this paper a new methodology for the evaluation of software structural complexity is described. It is based on the entropy evaluation of the random ...
People also ask
What is information entropy in information theory?
Generally, information entropy is the average amount of information conveyed by an event, when considering all possible outcomes. The concept of information entropy was introduced by Claude Shannon in his 1948 paper "A Mathematical Theory of Communication", and is also referred to as Shannon entropy.
What are the control flow graph elements in software testing?
The control flow graph is a graphical representation of a program's control structure. It uses the elements named process blocks, decisions, and junctions.
Feb 10, 2023 · In this article, we found proof of decreasing Shannon entropy while applying consistency rules in the construction of software architecture of IT systems.
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