  DNA emerges as a promising medium for the exponential growth of digital data
due to its density and durability. This study extends recent research by
addressing the \emph{coverage depth problem} in practical scenarios, exploring
optimal error-correcting code pairings with DNA storage systems to minimize
coverage depth. Conducted within random access settings, the study provides
theoretical analyses and experimental simulations to examine the expectation
and probability distribution of samples needed for files recovery. Structured
into sections covering definitions, analyses, lower bounds, and comparative
evaluations of coding schemes, the paper unveils insights into effective coding
schemes for optimizing DNA storage systems.
