Nature-inspired computing algorithms (NICs in short) inherit a certain length of history tracing back to Genetic Algorithm and Evolutionary Computing in the 50's. Since February 2008 by the birth of Firefly Algorithm, NICs started to receive lots of attentions from researchers around the global. Variants and even new species of NIC algorithms boomed like sprouts after rain. While it may be disputable to question the necessity of creations of further new species of such algorithms, it is observed that these algorithms are fundamentally made up of several core components. By exposing these components, the underlying design of a collection of so-called modern NIC optimization algorithms is revealed. In this paper, these core components of constructs from some popular NIC algorithms are reviewed, thereby debunking the myths of novelty and perhaps the excitement of inventing something really "New" by simply branding a NIC search method by merely a name of another living creature. This work also serves as a general guideline and reference for any algorithm architect who wants to create a new NIC algorithm in the future.