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<overview>

<p>

Efferent coupling is the number of outgoing dependencies for each class. In other words, it is the

number of other classes on which each class depends.

</p>

<p>

A class that depends on many other classes is quite brittle, because if any of

its dependencies change, the class itself may have to change as well. Furthermore, the

reason for the high number of dependencies is often that different parts of

the class depend on different groups of other classes, so it is common to

find that classes with high efferent coupling also lack cohesion.

</p>

</overview>

<recommendation>

<p>

You can reduce efferent coupling by splitting up a class so that each part depends on fewer classes.

</p>

</recommendation>

<example>

<p>In the following example, class <code>X</code> depends on both <code>Y</code> and

<code>Z</code>.

</p>

<sample src="ClassEfferentCoupling.py" />

<p>However, the methods that use <code>Y</code> do not use <code>Z</code>, and the methods

that use <code>Z</code> do not use <code>Y</code>. Therefore, the class can be split into

two classes, one of which depends only on <code>Y</code> and the other only on <code>Z</code></p>

<sample src="ClassEfferentCouplingGood.py" />

<p>

Although this is a slightly artificial example, this sort of situation

does tend to occur in more complicated classes,

so the general technique is quite widely applicable.

</p>

</example>

<references>

<li>

IBM developerWorks: <a href="https://web.archive.org/web/20190919085934/https://www.ibm.com/developerworks/library/j-eaed6/">Evolutionary architecture and emergent design: Emergent design through metrics</a>.

</li>

<li>

R. Martin, <em>Agile Software Development: Principles, Patterns and Practices</em>. Pearson, 2011.

</li>

</references>

</qhelp>