DETECTING PROGRAMMING FLAWS IN STUDENT SUBMISSIONS WITH STATIC SOURCE CODE ANALYSIS

Autor: Péter KASZAB, Máté CSERÉP
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Studia Universitatis Babes-Bolyai: Series Informatica, Vol 68, Iss 1 (2023)
Druh dokumentu: article
ISSN: 2065-9601
DOI: 10.24193/subbi.2023.1.03
Popis: Static code analyzer tools can detect several programming mistakes, that would lead to run-time errors. Such tools can also detect violations of the conventions and guidelines of the given programming language. Thus, the feedback provided by these tools can be valuable for both students and instructors in computer science education. In our paper, we evaluated over 5000 student submissions from the last two years written in C++ and C# programming languages at Eötvös Loránd University, Faculty of Informatics (Budapest, Hungary), by executing various static code analyzers on them. From the findings of the analyzers, we highlight some of the most typical and serious issues. Based on these results, we argue to include static analysis of programming submissions in automated and assisted semi-automatic evaluating and grading systems at universities, as these could increase the quality of programming assignments and raise the attention of students on various otherwise missed bugs and other programming errors.
Databáze: Directory of Open Access Journals