Research Article
Competitive Programming Vestige Using Machine Learning
@INPROCEEDINGS{10.1007/978-3-031-35081-8_22, author={Ajay Dharmarajula and Challa Sahithi and G. S. Prasada Reddy}, title={Competitive Programming Vestige Using Machine Learning}, proceedings={Intelligent Systems and Machine Learning. First EAI International Conference, ICISML 2022, Hyderabad, India, December 16-17, 2022, Proceedings, Part II}, proceedings_a={ICISML PART 2}, year={2023}, month={7}, keywords={Machine Learning Web Scraping Competitive Programming}, doi={10.1007/978-3-031-35081-8_22} }- Ajay Dharmarajula
Challa Sahithi
G. S. Prasada Reddy
Year: 2023
Competitive Programming Vestige Using Machine Learning
ICISML PART 2
Springer
DOI: 10.1007/978-3-031-35081-8_22
Abstract
Competitive programming improves our problem-solving abil ity. It helps in writing the source code of computer programs that help in solving given problems, and the majority of the problems are mathemat ical or logical in nature. In view of its staggering and different nature, programming requires a particular level of expertise in the examination of estimations, data structures, science, formal reasoning, and related tasks like testing and investigating. In light of the growing regard for expectations for programming, there exist different genuine programming platforms like HackerRank, CodeChef, CodeForces, Spoj, etc. where students can practice and work on their competitive programming skills. Monitoring the progress on these different platforms becomes hectic as they have to manually check each one. Also, there is no tool that helps in predicting their future scores based on their current practice. Another issue is that if the organisations or institutions wanted to monitor their student’s progress, it would be tougher as it would have to be done for each student manually. This work will help the students, as well as the organisations or institutions, maintain a proper portal with data to monitor their progress, by which students can improve their competitive programming skills, saving a lot of time compared to the time taken to do this monitoring manually.
