During the Covid-19 pandemic, the emergency remote teaching and learning mode created a myriad of challenges, due to students not being able to study on campus. This scenario, with limited physical contact between lecturers and students, and the fact that students did assignments and assessments virtually, with no invigilation, lead to students’ heightened reliance on source code plagiarism. In 2022, Covid-19 restrictions were still in place, which allowed the formation of one class, despite having access to limited computing resources. This situation changed in 2023, when Covid-19 restrictions were lifted, and the class needed to be split to allow all students access to a device in the computer laboratory. Because the timetable could only accommodate the groups T and S concurrently, two lecturers were utilised. Since the freeware source code plagiarism detection software available is time intensive to use, only one of the lecturers made use of the Moss tool to detect source code similarities. This study has the purpose to investigate the following: How prevalent was source code plagiarism in class T when compared to class S? To enable and answer to the question, quantitative data, namely source code plagiarism similarity percentages per assignment of each class is extracted and then compared to one another. The classes of 2024 could arrange the use of a paid source code plagiarism detection tool for a free trial, to allow the university to consider acquiring it. Although the programming lecturers consider such a tool a necessity, the financial implications of acquiring such a tool to be used by all programming students is substantial. The learning curve in terms of using it is also steep, and it is time consuming to set up. The outcome of this paper is aiming to facilitate the decision to be made by management.