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In general, maintainability index relies on many factors. For example, in Visual Studio, it rely on cyclomatic complexity, depth of inheritance, class coupling and lines of code; those four values must be as low as possible.

At the same time, I've never seen, neither in code metrics tools, nor in books, the comparison between only cyclomatic complexity (CC) and lines of code (LC).

Does it make sense to compute such ratio? What information does it give about the code? In other words, is it better to decrease more the CC than the LC to have a lower ratio?

What I notice is that for small projects, the ratio CC/LC is low (⅓ and lower). In other words, LC is high, and CC is low. In large projects, CC/LC is in most cases bigger than ½. Why?

Arseni Mourzenko
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4 Answers4

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There is a metric of cyclomatic complexity per source statements - it's called cyclomatic complexity density. This metric can be used to estimate the maintenance time and effort required for software projects.

Thomas Owens
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From http://en.wikipedia.org/wiki/Cyclomatic_complexity

Les Hatton claimed recently (Keynote at TAIC-PART 2008, Windsor, UK, Sept 2008) that McCabe Cyclomatic Complexity has the same prediction ability as lines of code.[11]

The ratio has about the same prediction ability as either used separately.

S.Lott
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As noted in a previous reply, this statement in the accepted answer is clearly incorrect.

The ratio has about the same prediction ability as either used separately.

CC density has been found to make sense by various researchers, although it does not seem to have gained significant popularity among practitioners. There is evidence from two well-known scholars in the software metrics area that the ratio (cyclomatic complexity density = CC / KLOC) is a much better predictor of maintenance productivity than the CC or KLOC alone.

G. K. Gill and C. F. Kemerer, "Cyclomatic complexity density and software maintenance productivity," in IEEE Transactions on Software Engineering, vol. 17, no. 12, pp. 1284-1288, Dec 1991. doi: 10.1109/32.106988

There are many others that have built on this work to refine CC density based metrics. Two examples:

  1. T. Andersson, K. Enholm and A. Törn. Length-independent measure of software complexity. In M. Ross, C.A. Brebbia, C. Staples, and J. Stapleton (eds.) Second International Conference on Software Quality Management, Vol 1, Managing Quality Systems, 1994.

  2. J. P. Mittal, Pradeep Bhatia, and Harish Mittal. 2009. Software maintenance productivity assessment using fuzzy logic. SIGSOFT Softw. Eng. Notes 34, 5 (October 2009), 1-4. DOI=http://dx.doi.org/10.1145/1598732.1598739

Nikos Houssos
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Sorry but I disagree with this statement:

The ratio has about the same prediction ability as either used separately.

A ratio is clearly not the same as an individual metric. Based on empirical data, Hatton claims that CC is proportional to XLOC with a constant ratio of about 0.25 (see slide 17) for his specific data set. Hence whether your XLOC is 60 or 400, your CC:XLOC ratio will be about 0.25 (ignoring statistical deviations at higher numbers). So the ratio is not predictive whatsoever.

Brian Rowe
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