Abstract
The article discusses three approaches to reducing runtime of the programs, which are solutions of Olympiad tasks on computer science, related to sequences or matrices. The first approach is based on the representation of some sequences in matrix form and then the program of calculating the members of the sequence will have asymptotics equal to the time complexity of the exponentiation algorithm and will be O(log (n)). The second approach is to upgrade the known code to obtain significant reduction of the program runtime. This approach is very important to know for scientists who write code for scientific researches and are faced with matrix multiplication operations. The third approach is based on reducing time complexity by search for regularities; the author's task is presented and this approach is used to solve it.
Highlights
Sports programming has become a promising intellectual sport
This paper proposes three ways to reduce the runtime for computer science tasks that require the use of sequences and / or arrays: - performing calculations using a matrix representation of sequences; - reducing program execution time by using the features of the programming language; - reducing time complexity by looking for regularities
This paper discusses three approaches to reducing solution execution times for computer science tasks that require some knowledge of sequences and / or arrays to solve them
Summary
Sports programming has become a promising intellectual sport. Every year, the number of pupils and students interested in Olympiads in computer science, as perhaps the most common type of sports programming, is growing. The most promising and successful participants are offered internships, combined with university study and the opportunity to gain full-time employment at the company after training. Many former Olympians are organizing successful projects related to programming and IT Due to their participation in the Olympics, they were able to develop resistance to complex psychological stress. It seems that to achieve solid results at the Olympics, it is enough to study a certain number of existing algorithms and theoretical material, and only to successfully use them in competitions, leaving others no chance of winning The third approach already needs a creative approach, has no general recommendations and is often used with the first two approaches
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