Identifying complex functions: By investigating various aspects of code complexity

Antinyan, Vard; Staron, Miroslaw; Derehag, Jesper; Runsten, Mattias; Wikstrom, Erik; Meding, Wilhelm; Henriksson, Anders; Hansson, Jörgen

doi:10.1109/sai.2015.7237246

Cited by 7 publications

(6 citation statements)

References 23 publications

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“…McCabe [52], or cyclomatic complexity, is a measure of the number of independent paths in a source code component. The assumption is that a source code component with high McCabe score would be hard to maintain; it would be more change-and bugprone [5,6,21,47,61,62,68,84,93]. Another popular code metric is the Halstead metric, which is mainly based on the number of operators and operands in a code component [7,21,35,43,63].…”

Section: Related Workmentioning

confidence: 99%

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An Empirical Study on Maintainable Method Size in Java

Chowdhury¹,

Uddin²,

Holmes³

2022

Preprint

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Code metrics have been widely used to estimate software maintenance effort. Metrics have generally been used to guide developer effort to reduce or avoid future maintenance burdens. Size is the simplest and most widely deployed metric. The size metric is pervasive because size correlates with many other common metrics (e.g., McCabe complexity, readability, etc.). Given the ease of computing a method's size, and the ubiquity of these metrics in industrial settings, it is surprising that no systematic study has been performed to provide developers with meaningful method size guidelines with respect to future maintenance effort. In this paper we examine the evolution of ∼785K Java methods and show that developers should strive to keep their Java methods under 24 lines in length. Additionally, we show that decomposing larger methods to smaller methods also decreases overall maintenance efforts. Taken together, these findings provide empirical guidelines to help developers design their systems in a way that can reduce future maintenance. CCS Concepts• Software engineering → Code metrics.

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Section: Related Workmentioning

confidence: 99%

“…#Revisions: The number of revisions, a common maintenance indicator [5,6,58,76], is the total number of times a method has been modified, regardless of the type of modification-corrective, adaptive, preventive, or perfective [22].…”

Section: Change-pronenessmentioning

confidence: 99%

An Empirical Study on Maintainable Method Size in Java

Chowdhury¹,

Uddin²,

Holmes³

2022

Preprint

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show abstract

“…#Revisions: Number of revisions of a component is considered as an indication of maintenance effort by many (Antinyan et al 2014;Monden et al 2002;Shin et al 2011;Antinyan et al 2015). The consensus is that a well designed less complex component should not need many revisions.…”

Section: Maintenance Indicator Selectionmentioning

confidence: 99%

“…To both of these metrics, two methods each with two loops (for example) are equally complex, even if one of them has nested loops and the other does not. Measuring Maximum Nested Block Depth (referred to as NBD) is a common solution(Johnson et al 2019;Antinyan et al 2015). Proxy Indentation:Hindle et al (2008) argued that a metric like McCabe is hard to calculate because one needs a language-specific parser.…”

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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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“…Padhy et al (2015) carried out a systematic review on metrics and concluded that cyclic complexity, DIT, NOC, AC, EC, and LCOM are well established and valid. identies the same types of complexity that Antinyan et al (2015): internal and external. The internal is the complexity of the function/method itself and the external one is its relation of dependence with other functions/methods.…”

Section: Complexitymentioning

confidence: 99%

Mob Programming for writing code with high complexity and remote work

Kattan¹

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Identifying complex functions: By investigating various aspects of code complexity

Cited by 7 publications

References 23 publications

An Empirical Study on Maintainable Method Size in Java

An Empirical Study on Maintainable Method Size in Java

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

Mob Programming for writing code with high complexity and remote work

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