Evaluation of Halstead and Cyclomatic Complexity Metrics in Measuring Defect Density

Alfadel, Mahmoud; Kobilica, Armin; Hassine, Jameleddine

doi:10.1109/ieeegcc.2017.8447959

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…This metric was proposed in 1976, and has been widely studied and adopted (Ebert et al 2016;Pantiuchina et al 2018). We can divide all the McCabe-related studies into two groups: studies that support its validity (e.g., Curtis et al 1979;Landman et al 2014;Tiwari and Kumar 2014;Zhou et al 2010;Alfadel et al 2017), and studies that do not (e.g., Weyuker 1988;Shepperd 1988;Gil and Lalouche 2017;Scalabrino et al 2017). McCabe is not the only metric that has been debated.…”

Section: Related Work and Motivationmentioning

confidence: 99%

Revisiting the debate: Are code metrics useful for measuring maintenance effort?

et al. 2022

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Evaluating and predicting software maintenance effort using source code metrics is one of the holy grails of software engineering. Unfortunately, previous research has provided contradictory evidence in this regard. The debate is still open: as a community we are not certain about the relationship between code metrics and maintenance impact. In this study we investigate whether source code metrics can indeed establish maintenance effort at the previously unexplored method level granularity. We consider ∼730K Java methods originating from 47 popular open source projects. After considering seven popular method level code metrics and using change proneness as a maintenance effort indicator, we demonstrate why past studies contradict one another while examining the same data. We also show that evaluation context is king. Therefore, future research should step away from trying to devise generic maintenance models and should develop models that account for the maintenance indicator being used and the size of the methods being analyzed. Ultimately, we show that future source code metrics can be applied reliably and that these metrics can provide insight into maintenance effort when they are applied in a judiciously context-sensitive manner.

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