Software quality metrics in the automatic evaluation of Python introductory programming

Métricas de qualidade de software na avaliação automática da programação introdutória Python

Authors

  • Andrew Nunes de Barros Reis
  • Silvério Sirotheau Corrêa Neto
  • Eloi Luiz Favero
  • João Carlos Alves dos Santos
  • Pollianni Leão da Silva
  • Thiago Rafael da Silva Moura

DOI:

https://doi.org/10.34115/basrv6n5-006

Keywords:

automatic assessment, feedback, refactoring, code

Abstract

Numerous virtual environments with automatic program evaluation have emerged to assist the teaching-learning process, allowing timely feedback. In a review of these environments, we find few studies that focus on an approach centered on refactoring: where students are strongly encouraged to refactor, improving the submitted code to also meet quality criteria. In a traditional environment, the student submits the answer and if it is dynamically correct, he goes to the next question. In this work, we propose a complementary approach based on software engineering metrics, which allow a finer evaluation of the code where the programmer, after having his dynamically correct answer, is invited and encouraged to refactor his solution towards an optimal code that also meets the software quality metrics. The work is based on source code in the Python language and shows which software quality metrics can be used with the purpose of encouraging students to refactor their code in programming fundamentals disciplines.

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Published

2022-09-21

Issue

Section

Artigos originais