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Introducing a Practical Educational Tool for Correlating Algorithm Time Complexity with Real Program Execution
Author(s) -
Gisela Kurniawati,
Oscar Karnalim
Publication year - 2018
Publication title -
journal of information technology and computer science
Language(s) - English
Resource type - Journals
eISSN - 2540-9824
pISSN - 2540-9433
DOI - 10.25126/jitecs.20183140
Subject(s) - programmer , computer science , task (project management) , java , execution time , set (abstract data type) , code (set theory) , algorithm , source code , big data , machine learning , programming language , data mining , management , economics
Algorithm time complexity is an important topic to be learned for programmer; it could define whether an algorithm is practical to be used on real environment or not. However, learning such material is not a trivial task. Based on our informal observation regarding students’ test, most of them could not correlate Big-Oh equation to real program execution. This paper proposes JCEL, an educational tool that acts as a supportive tool for learning algorithm time complexity. Using this tool, user could learn how to correlate Big-Oh equation with real program execution by providing three components: a Java source code, source code input set, and time complexity equations. According to our evaluation, students feel that JCEL is helpful for learning the correlation between Big-Oh equation and real program execution. Further, the use of Pearson correlation in JCEL shows a promising result.

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