A suite of cognitive complexity metrics

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Date

2012

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Information Systems Engineering
Information Systems is an academic and professional discipline which follows data collection, utilization, storage, distribution, processing and management processes and modern technologies used in this field. Our department implements a pioneering and innovative education program that aims to raise the manpower, able to meet the changing and developing needs and expectations of our country and the world. Our courses on current information technologies especially stand out.
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Computer Engineering
(1998)
The Atılım University Department of Computer Engineering was founded in 1998. The department curriculum is prepared in a way that meets the demands for knowledge and skills after graduation, and is subject to periodical reviews and updates in line with international standards. Our Department offers education in many fields of expertise, such as software development, hardware systems, data structures, computer networks, artificial intelligence, machine learning, image processing, natural language processing, object based design, information security, and cloud computing. The education offered by our department is based on practical approaches, with modern laboratories, projects and internship programs. The undergraduate program at our department was accredited in 2014 by the Association of Evaluation and Accreditation of Engineering Programs (MÜDEK) and was granted the label EUR-ACE, valid through Europe. In addition to the undergraduate program, our department offers thesis or non-thesis graduate degree programs (MS).

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Abstract

In this paper, we propose a suite of cognitive metrics for evaluating complexity of object-oriented (OO) codes. The proposed metric suite evaluates several important features of OO languages. Specifically, the proposed metrics are to measure method complexity, message complexity (coupling), attributes complexity and class complexity. We propose also a code complexity by considering the complexity due to inheritance for the whole system. All these proposed metrics (except attribute complexity) use the cognitive aspect of the code in terms of cognitive weight. All the metrics have critically examined through theoretical and empirical validation processes. © 2012 Springer-Verlag.

Description

Universidade Federal da Bahia (UFBA); Universidade Federal do Reconcavo da Bahia (UFRB); Universidade Estadual de Feira de Santana (UEFS); University of Perugia; University of Basilicata (UB)

Keywords

attributes, class, cognitive complexity, coupling, inheritance, messages, methods, software metrics, validation

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Citation

19

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Source

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -- 12th International Conference on Computational Science and Its Applications, ICCSA 2012 -- 18 June 2012 through 21 June 2012 -- Salvador de Bahia -- 90945

Volume

7336 LNCS

Issue

PART 4

Start Page

234

End Page

247

URI

https://doi.org/10.1007/978-3-642-31128-4_17
 https://hdl.handle.net/20.500.14411/3672

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Scopus