NexTech 2021 Congress
October 03, 2021 to October 07, 2021 - Barcelona, Spain

  • UBICOMM 2021, The Fifteenth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies
  • ADVCOMP 2021, The Fifteenth International Conference on Advanced Engineering Computing and Applications in Sciences
  • SEMAPRO 2021, The Fifteenth International Conference on Advances in Semantic Processing
  • AMBIENT 2021, The Eleventh International Conference on Ambient Computing, Applications, Services and Technologies
  • EMERGING 2021, The Thirteenth International Conference on Emerging Networks and Systems Intelligence
  • DATA ANALYTICS 2021, The Tenth International Conference on Data Analytics
  • GLOBAL HEALTH 2021, The Tenth International Conference on Global Health Challenges
  • CYBER 2021, The Sixth International Conference on Cyber-Technologies and Cyber-Systems

SoftNet 2021 Congress
October 03, 2021 to October 07, 2021 - Barcelona, Spain

  • ICSEA 2021, The Sixteenth International Conference on Software Engineering Advances
  • ICSNC 2021, The Sixteenth International Conference on Systems and Networks Communications
  • CENTRIC 2021, The Fourteenth International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services
  • VALID 2021, The Thirteenth International Conference on Advances in System Testing and Validation Lifecycle
  • SIMUL 2021, The Thirteenth International Conference on Advances in System Simulation
  • SOTICS 2021, The Eleventh International Conference on Social Media Technologies, Communication, and Informatics
  • INNOV 2021, The Tenth International Conference on Communications, Computation, Networks and Technologies
  • HEALTHINFO 2021, The Sixth International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing

NetWare 2021 Congress
November 14, 2021 to November 18, 2021 - Athens, Greece

  • SENSORCOMM 2021, The Fifteenth International Conference on Sensor Technologies and Applications
  • SENSORDEVICES 2021, The Twelfth International Conference on Sensor Device Technologies and Applications
  • SECURWARE 2021, The Fifteenth International Conference on Emerging Security Information, Systems and Technologies
  • AFIN 2021, The Thirteenth International Conference on Advances in Future Internet
  • CENICS 2021, The Fourteenth International Conference on Advances in Circuits, Electronics and Micro-electronics
  • ICQNM 2021, The Fifteenth International Conference on Quantum, Nano/Bio, and Micro Technologies
  • FASSI 2021, The Seventh International Conference on Fundamentals and Advances in Software Systems Integration
  • GREEN 2021, The Sixth International Conference on Green Communications, Computing and Technologies

TrendNews 2021 Congress
November 14, 2021 to November 18, 2021 - Athens, Greece

  • CORETA 2021, Advances on Core Technologies and Applications
  • DIGITAL 2021, Advances on Societal Digital Transformation

 


ThinkMind // ICSEA 2021, The Sixteenth International Conference on Software Engineering Advances // View article icsea_2021_1_10_18001


An Empirical Study of the Correlation of Cognitive Complexity-related Code Measures

Authors:
Luigi Lavazza

Keywords: Cognitive complexity; software code measures; McCabe complexity; cyclomatic complexity; Halstead mea- sures; static code measures

Abstract:
Several measures have been proposed to represent various characteristics of code, such as size, complexity, cohesion, coupling, etc. These measures are deemed interesting because the “internal” characteristics they measure (which are not interesting per se) are believed to be correlated with “external” software qualities (like reliability, maintainability, etc.) that are definitely interesting for developers or users. Although many measures have been proposed for software code, new measures are continuously proposed. However, before starting using a new measure, we would like to ascertain that it is actually useful and that it provides some improvement with respect to well established measures that have been in use for a long time and whose merits have been widely evaluated. In 2018, a new code measure, named “Cognitive Complexity” was proposed. According to the proposers, this measure should correlate to code understandability much better than ‘traditional’ code measures, such as McCabe Complexity, for instance. However, hardly any experimentation proved whether the “Cognitive Complexity” measure is better than other measures or not. Actually, it was not even verified whether the new measure provides different knowledge concerning code with respect to ‘traditional’ measures. In this paper, we aim at evaluating experimentally to what extent the new measure is correlated with traditional measures. To this end, we measured the code from a set of open-source Java projects and derived models of “Cognitive Complexity” based on the traditional code measures yielded by a state-of-the-art code measurement tool. We found that fairly accurate models of “Cognitive Complexity” can be obtained using just a few traditional code measures. In this sense, the “Cognitive Complexity” measure does not appear to provide additional knowledge with respect to previously proposed measures.

Pages: 1 to 6

Copyright: Copyright (c) IARIA, 2021

Publication date: October 3, 2021

Published in: conference

ISSN: 2308-4235

ISBN: 978-1-61208-894-5

Location: Barcelona, Spain

Dates: from October 3, 2021 to October 7, 2021

SERVICES CONTACT
2010 - 2017 © ThinkMind. All rights reserved.
Read Terms of Service and Privacy Policy.