Systems represented as graphs

Modularity is one measure of the structure of networks or graphs. It was designed to measure the strength of division of a network into modules (also called groups, clusters or communities). Networks with high modularity have dense connections between the nodes within modules but sparse connections between nodes in different modules. ... Biological networks, including animal brains, exhibit a high degree of modularity.

Every computer program may be represented as a graph of nodes connected by edges. Every call to a procedure, subroutine or library function can be represented by an edge between the nodes representing the caller and the callee.

This book describes some architectural programming techniques that have the aim of creating clusters within the graph that have high internal edge density and low external edge density. The reasoning behind this approach is the observation, in practice, that complexity in computer systems tends to rise exponentionally with system size. Complexity is subject to a network effect. While it can be possible to manage a degree of complexity at a small scale, such management tends not to scale to larger systems. Therefore, we need to break our large systems up into small components and at the same time carefully manage the relationships between them.

We define the term coupling as the density of edges between components. We continually look for ways to reduce coupling, which is to say, reduce the count of edges between components.

The twin of coupling is cohesion. Cohesion is the measure of the density of graph edges inside a component. We are comfortable when this increases, because when we treat the system as a whole we see that an increase in cohesion is balanced by a reduction in coupling. Both are indicators that we are increasing modularity.

find some mathematical treatment of graph density

'Micro' and 'macro' modularity

Modularity, as a property of a graph, can be measured at any level of granularity. However, in practice it is useful to draw distinctions between modularity within a single address space, modularity within a set of processes on a single host, modularity within a set of locally distributed processes (processes residing on multiple hosts attached to a local network) and modularity within a set of geographically distributed processes.

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