Heuristic Minimization of Symmetric Index Generation Functions utilizing their Properties

This paper focuses on the minimization of index generation functions, which are useful in telecommunication and cybersecurity. In particular, we target a specific class of those functions, i.e., symmetric index generation functions. The application of logic synthesis methods to such functions can often lead to a representation that uses fewer variables. We analyze the properties of those functions and how they can be used to minimize the number of variables. What is more, we investigate the influence on accelerating other minimization techniques, such as linear decomposition. Presented results show that by taking advantage of the described properties, the computations using the heuristic algorithm are significantly faster.