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https://doi.org/10.1109/seaa.2...
Article . 2015 . Peer-reviewed
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Re-visiting the 'Maintainability Index' Metric from an Object-Oriented Perspective

Authors: Steve Counsell; Xiaohui Liu 0001; Sigrid Eldh; Roberto Tonelli; Michele Marchesi; Giulio Concas; Alessandro Murgia;

Re-visiting the 'Maintainability Index' Metric from an Object-Oriented Perspective

Abstract

The Maintainability Index (MI) metric was proposed in the early nineties to gauge ease of code maintenance. A high value of MI indicates well-constructed code which is easy to maintain and a low MI, the opposite. The metric has been criticized in the past and more recently for its applicability to code and validity more generally. Very few studies however have explored whether the MI correlates strongly with class features such as coupling, defects or size - features of object-oriented (OO) classes which are acknowledged to be surrogates of maintenance complexity. We explore the relationship between the MI and these four perspectives. Three releases of two Eclipse projects were used as the empirical basis of the study and the JHawk tool was used to extract class-based metrics. Significant correlations were found between class features and the MI for all class features except fan-in which measures incoming coupling and determined externally by 'using' classes, however, further exploration of the data revealed that the application of the MI to an OO paradigm was not particularly successful, due primarily to the influence of class size. For OO systems, we would thus warn against the use of MI as a measure of maintenance.

Country
Belgium
Keywords

Computer. Automation

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Average
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