{'fraction_non_alphanumeric': 0.015030946065428824, 'fraction_numerical': 0.0, 'mean_word_length': 5.505747126436781, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Algorithmic development of effectiveness prediction for system of systems

A system of systems (SOS) is a coalition of independently operated and managed systems that function together as one unit to efficiently and effectively meet a specific need. Combining disparate systems can produce challenges across the entire system life-cycle. Specifically, system of systems introduces complications in performance management because of the autonomy of their individual system components and the complexity of their interactions as they function as a single unit. This paper examines the ways in which key performance metrics for the system's performance are affected by the autonomy of individual member systems. It assesses the impact the individual systems have on the system-of-systems. Included is a mapping of the system performance metrics to the system-of-system measures of effectiveness, and the development of an algorithm based on that mapping to determine the overall system effectiveness. The nonlinear objective function seeks to find the optimal system configuration while assessing all component systems simultaneously.