A unique complexity metric

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2008

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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

Metrics, in general, are defined as "a quantitative measure of the degree to which a system, component, or process possesses a given attribute". Complexity metrics are used to predict critical information about reliability and maintainability of software systems. This paper proposes complexity metric, which includes all major factors responsible for complexity. We validated our metric against the principles of measurement theory since the measurement theory has been proposed and extensively used in the literature as a means to evaluate the software engineering metrics. The scale of the metric is investigated through Extensive structure. It is found that the proposed measure is on ratio scale. The applicability of the proposed measure is tested through test cases and comparative study. © 2008 Springer-Verlag Berlin Heidelberg.

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University of Perugia; University of Calgary; Innovative Computational Science Applications (ICSA); MASTER-UP; University of Calgary, SPARCS Laboratory; OptimaNumerics

Keywords

Evaluation criteria, Extensive structure, Measurement theory, Scale, Software complexity metric

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -- International Conference on Computational Science and Its Applications, ICCSA 2008 -- 30 June 2008 through 3 July 2008 -- Perugia -- 73953

Volume

5073 LNCS

Issue

PART 2

Start Page

641

End Page

651

URI

https://doi.org/10.1007/978-3-540-69848-7_52

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