<prompt> Theha mongolo oa Big-O ho hlalosa ho rarahana ha algorithm e itsengnan  <response>: Instruction in English: Construct a Big-O notation to explain the complexity of a certain algorithm . Response in English: The Big-O notation is a standard way to describe the performance or complexity of an algorithm. In Big-O notation, the complexity of an algorithm is represented by an algebraic expression, where the leading term provides the basic approximation to its growth rate.The most commonly used time complexities represented in Big-O notation in ascending order of their upper bound growth rate are:- Constant: O1 - This implies that the running time of the algorithm is constant, regardless of the size of the input.- Logarithmic: Olog n - This means that the run time of the algorithm increases logarithmically with the size of the input.- Linear: On - This implies that the run time of the algorithm increases linearly with the size of the input.- Linear-logarithmic Log-linear: Onlogn - This means that the run time of the algorithm increases log-linearly with the size of the input.- Quadratic: On2 - This implies that the run time of the algorithm increases quadratically with the size of the input.- Exponential: O2n - This means that the run time of the algorithm increases exponentially with the size of the input.For instance, lets suppose an algorithm has a time complexity of On2. This means that the algorithms run time will be proportional to the square of the size of its input. That is, if the size of the input increases, the run time of the algorithm would increase quadratically.In summary, the Big-O notation is an effective way of expressing the upper bound of an algorithms growth rate, which helps to evaluate the performance of the algorithm. . Response in Sesotho: Note ea Big-O ke mokhoa o tloaelehileng oa ho hlalosa tsebetso kapa ho rarahana ha algorithm. Ho Big-O notation, ho rarahana ha algorithm ho emeloa ke polelo ea algebra, moo lentsoe le etellang pele le fanang ka tekanyo ea motheo ho sekhahla sa kholo ea eona. Mathata a sebelisoang ka ho fetesisa a emeloang ho mongolo oa Big-O ka tatellano e nyolohang ea sekhahla sa kholo ea eona e holimo ke: - Kamehla: O1 - Sena se fana ka maikutlo a hore nako ea ho sebetsa ea algorithm ha e fetohe, ho sa tsotelehe boholo ba kenyeletso. . - Logarithmic: Olog n - Sena se bolela hore nako ea ho matha ea algorithm e eketseha ka logarithmically ka boholo ba ho kenya letsoho. - Linear: On - Sena se bolela hore nako ea ho matha ea algorithm e eketseha ka mokhoa o lekanang le boholo ba ho kenya letsoho. - Linear-logarithmic Log-linear: Onlogn - Sena se bolela hore nako ea ho sebetsa ea algorithm e eketsa log-linearly le boholo ba ho kenya letsoho. - Quadratic: On2 - Sena se bolela hore nako ea tsebetso ea algorithm e eketseha ka makhetlo a mane ka boholo ba kenyeletso. - Exponential: O2n - Sena se bolela hore nako ea ho sebetsa ea algorithm e eketseha haholo ka boholo ba ho kenya letsoho. Mohlala, ha re re algorithm e na le ho rarahana ha nako ea On2. Sena se bolela hore nako ea ho sebetsa ea algorithm e tla lekana le lisekoere tsa boholo ba tlhahiso ea eona. Ke hore, haeba boholo ba ho kenya letsoho bo eketseha, nako ea ho sebetsa ea algorithm e ne e tla eketseha ka makhetlo a mane. Ka bokhutsoane, notation ea Big-O ke mokhoa o sebetsang oa ho hlahisa moeli o kaholimo oa sekhahla sa kholo ea algorithm, e thusang ho lekola tsebetso ea algorithm. 