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Program Comprehension and Quality Experiments in Programming Education

Authors Maria Medvidova, Jaroslav Porubän

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Author Details

Maria Medvidova
  • Department of Computers and Informatics, Technical University of Kosice, Slovakia
Jaroslav Porubän
  • Department of Computers and Informatics, Technical University of Kosice, Slovakia

Funding

This work was supported by project VEGA No. 1/0630/22: Lowering Programmers’ Cognitive Load Using Context-Dependent Dialogs.

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Maria Medvidova and Jaroslav Porubän. Program Comprehension and Quality Experiments in Programming Education. In Third International Computer Programming Education Conference (ICPEC 2022). Open Access Series in Informatics (OASIcs), Volume 102, pp. 14:1-14:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/OASIcs.ICPEC.2022.14

Abstract

The paper deals with the design of a new experimental method designed to measure the understanding of the code of subjects who do not know any programming language in connection with the implementation of empirical and analytical study. The aim of this work is the analysis of students' knowledge before and after the course Basics of Algorithmization and Programming at Technical University in Kosice, Slovakia, and the subsequent static analysis of their codes from one of the assignments. The theoretical part provides a look at the various models and ways to measure program comprehension, code quality metrics, examines the most common analysis tools, suggests recommendations for improving comprehensibility, and provides a closer look at program comprehension issues in the teaching context.

Subject Classification

ACM Subject Classification
  • General and reference → Surveys and overviews
Keywords
  • Program comprehension
  • static code analysis
  • empirical software engineering
  • code as a story
  • students

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