Improving the efficiency of learning programming and algorithmization through the use of an automated testing system

Abstract

Problem. One of the main fundamental disciplines in training of future IT-specialists are the disciplines “Programming” and “Algorithms and data structures”. The issue of testing the programs developed by students becomes relevant. Obviously, the so-called manual testing is too time-consuming and inefficient, so the increasing number of teachers use automated testing systems. Goal. The goal is to analyze the existing approaches and find an effective solution to the problem of automated testing of student programs when studying the basics of programming and algorithmization. Methodology. The analysis carried out showed that there are two main approaches to the organization of automated testing of student programs. The first is the use of special information systems that automatically check the programs. The second is the use of Internet resources designed to use ready-made tasks in the process of learning or training. Results. The use of automated testing systems in the study of programming, algorithms and data structures was substantiated. The existing approaches were analyzed and their advantages and disadvantages were identified. It was proposed to use the DOTS system, which, according to the authors, is the most effective tool to achieve this goal. Originality. The advantages of the proposed approach are the presence of a large database of tasks of various levels of complexity, the ease and convenience of creating new tournaments, filling them with tasks and adding students to these tournaments, the ability to automatically check all tasks and generate final tables with the results. This gives the possibility for the teacher to control all stages of the assignment by students, view the source code of the programs sent for verification and manage the entire process. Practical value. The use of an automated testing system in the study of the basics of programming and algorithmization ultimately makes it possible to effectively form the competence of graduates in the design, development and analysis of algorithms, as well as in the implementation of algorithms in the form of software and information systems.