Complex network theory is based on graph theory and statistical analysis Complex real-world systems represented by typed and/or attributed graphs form different kinds of complex networks. Statistical methods applied on these graphs provide powerful mechanism in network analysis. Complex networks theory has an application in many areas such are social networks, computer networks, etc. In a context of software engineering and software development we can talk about special type of complex networks – software networks.

Software networks are directed graphs representing relationships between software entities (packages, classes, modules, methods, functions, procedures, etc.). Software network can be observed as a static representation of software code and design and can be used in analysis of the quality of software development process and software product with particular application in a field of large-scale software systems.

Software metrics are basic mechanism in software quality analysis. Software metric can be defined as measure that reflects some property of a software product or its specification. Software metrics can be calculated based on a static representation of source code and design in which case they become part of static analysis.

The aim of this paper is to investigate possibility of application of complex networks theory in static analysis of software quality. Basic goal is to set relations between particular software metrics and corresponding statistical measures from complex networks theory. This would be a basis for stronger formalisation of software metrics and establishing stronger ties between these two fields that have a common goal. Furthermore, this paper will provide an overview of available approaches in this direction.