On the potential of process simulation in software project schedule optimization

Abstract

In this paper, we highlight the application potential of process simulation techniques for software cybernetics research. Software engineering has seen many fruitful applications of simulation when modeling, understanding, and improving the software development process. In particular, process simulation has proven to be a valuable and efficient tool in our own software cybernetics research, having helped us to understand how scheduling policies actually behave in our discrete-time Markov decision process model for software projects. We outline how to advance the use of process simulation in our model to a much higher level: when computing optimal scheduling policies, simulation can be applied in the optimization step of the dynamic programming algorithms in order to save computation time. This approach resembles optimization techniques from the field of reinforcement learning, providing further evidence of the potential of simulation in software cybernetics.