License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.ICPEC.2022.14
URN: urn:nbn:de:0030-drops-166180
URL: https://drops.dagstuhl.de/opus/volltexte/2022/16618/
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Medvidova, Maria ; Porubän, Jaroslav

Program Comprehension and Quality Experiments in Programming Education

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OASIcs-ICPEC-2022-14.pdf (0.5 MB)


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.

BibTeX - Entry

@InProceedings{medvidova_et_al:OASIcs.ICPEC.2022.14,
  author =	{Medvidova, Maria and Porub\"{a}n, Jaroslav},
  title =	{{Program Comprehension and Quality Experiments in Programming Education}},
  booktitle =	{Third International Computer Programming Education Conference (ICPEC 2022)},
  pages =	{14:1--14:12},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-229-7},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{102},
  editor =	{Sim\~{o}es, Alberto and Silva, Jo\~{a}o Carlos},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/16618},
  URN =		{urn:nbn:de:0030-drops-166180},
  doi =		{10.4230/OASIcs.ICPEC.2022.14},
  annote =	{Keywords: Program comprehension, static code analysis, empirical software engineering, code as a story, students}
}

Keywords: Program comprehension, static code analysis, empirical software engineering, code as a story, students
Collection: Third International Computer Programming Education Conference (ICPEC 2022)
Issue Date: 2022
Date of publication: 11.07.2022


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