Monte-Carlo randomized algorithm: Empirical analysis on real-world information systems

Determination of development priority of information system subsystems is a problem that warrants resolution during information system development. It has been proven, previously, that this problem of information system development order is in fact NP-complete, NP-hard, and APX-hard. To solve this problem on a general case we have previously developed Monte-Carlo randomized algorithm, calculated complexity of this algorithm, and so on. After previous research we were able to come into possession of digraphs that represent real-world information systems. Therefore, in this paper we will empirically analyze Monte-Carlo algorithm to determine how the algorithm works on real-world examples. Also, we will critically review the results and give some possible areas of future research as well.