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Identifying Complex Functions By Investigating Various Aspects of Code Complexity
Department of Computer Science and Engineering, Chalmers University, Gothenburg, Sweden.
Department of Computer Science and Engineering, Chalmers University, Gothenburg, Sweden.
Ericsson, Gothenburg, Sweden.
AB Volvo, Gothenburg, Sweden.
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2015 (English)In: Proceedings of 2015 Science and Information Conference (SAI): July 28-30, 2015, London, United Kingdom, IEEE Press, 2015, 879-888 p.Conference paper (Refereed)Text
Abstract [en]

The complexity management of software code has become one of the major problems in software development industry. With growing complexity the maintenance effort of code increases. Moreover, various aspects of complexity create difficulties for complexity assessment. The objective of this paper is to investigate the relationships of various aspects of code complexity and propose a method for identifying the most complex functions. We have conducted an action research project in two software development companies and complemented it with a study of three open source products. Four complexity metrics are measured, and their nature and mutual influence are investigated. The results and possible explanations are discussed with software engineers in industry. The results show that there are two distinguishable aspects of complexity of source code functions: Internal and outbound complexities. Those have an inverse relationship. Moreover, the product of them does not seem to be greater than a certain limit, regardless of software size. We present a method that permits identification of most complex functions considering the two aspects of complexities. The evaluation shows that the use of the method is effective in industry: It enables identification of 0.5% most complex functions out of thousands of functions for reengineering.

Place, publisher, year, edition, pages
IEEE Press, 2015. 879-888 p.
Keyword [en]
code, complexity, management, risk, trade-off
Identifiers
URN: urn:nbn:se:his:diva-12796DOI: 10.1109/SAI.2015.7237246ISI: 000380448800122ScopusID: 2-s2.0-84957825136ISBN: 978-1-4799-8547-0OAI: oai:DiVA.org:his-12796DiVA: diva2:953920
Conference
Science and Information Conference (SAI), July 28-30, 2015, London, United Kingdom
Available from: 2016-08-19 Created: 2016-08-19 Last updated: 2016-11-29

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Hansson, Jörgen
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