TL;DR
This paper empirically analyzes altcoin source code similarities, inheritance relationships, and their correlation with market prospects, revealing high code similarity and evolutionary patterns akin to biology, with higher innovation indicating better market potential.
Contribution
It introduces a comprehensive dataset and a novel temporal clustering algorithm to study altcoin code inheritance and its relation to market prospects, highlighting evolutionary features and innovation impacts.
Findings
Over 85% of altcoin repositories have high code similarity.
Altcoin family structures exhibit biological evolution features.
Higher code innovation correlates with better market prospects.
Abstract
The great influence of Bitcoin has promoted the rapid development of blockchain-based digital currencies, especially the altcoins, since 2013. However, most altcoins share similar source codes, resulting in concerns about code innovations. In this paper, an empirical study on existing altcoins is carried out to offer a thorough understanding of various aspects associated with altcoin innovations. Firstly, we construct the dataset of altcoins, including source code repositories, GitHub fork relations, and market capitalizations (cap). Then, we analyze the altcoin innovations from the perspective of source code similarities. The results demonstrate that more than 85% of altcoin repositories present high code similarities. Next, a temporal clustering algorithm is proposed to mine the inheritance relationship among various altcoins. The family pedigrees of altcoin are constructed, in which…
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