Software execution processes as an evolving complex network

Inspired by the surprising discovery of several recurring structures in various complex networks, in recent years a number of related works treated software systems as a complex network and found that software systems might expose the small-world effects and follow scale-free degree distributions. Different from the research perspectives adopted in these works, the work presented in this paper treats software execution processes as an evolving complex network for the first time. The concept of software mirror graph is introduced as a new model of complex networks to incorporate the dynamic information of software behavior. The experimentation paradigm with statistical repeatability was applied to three distinct subject programs to conduct several software experiments. The corresponding experimental results are analyzed by treating the software execution processes as an evolving directed topological graph as well as an evolving software mirror graph. This results in several new findings. While the software execution processes may demonstrate as a small-world complex network in the topological sense, they no longer expose the small-world effects in the temporal sense. Further, the degree distributions of the software execution processes may follow a power law. However, they may also follow an exponential function or a piecewise power law.