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Analysis and classification of bad code smells and perfumes in student Python code

Simo, Leslie Natacha
(2024)

Files

Simo_19832200_2024.pdf
  • UCLouvain restricted access
  • Adobe PDF
  • 1.06 MB

Details

Supervisors
Mens, Kim ; Nijssen, Siegfried
Faculty
Ecole polytechnique de Louvain
Degree label
Master [120] en sciences informatiques, à finalité spécialisée
Abstract
In introductory programming courses, students often show diverse coding practices in their Python code submissions. These can vary from well-executed solutions to less-than-ideal ones that might impact how their code operates. Even when students try their best, some may still encounter difficulties or make mistakes because they misunderstand or misinterpret certain programming concepts. This thesis identifies and classifies different coding practices by analyzing patterns in student code submissions to improve the code quality and learning outcomes of students, as well as help educators provide customized feedback and suggestions to students.