You are here:
Publication details
Evaluating Code Improvements in Software Quality Course Projects
Authors | |
---|---|
Year of publication | 2022 |
Type | Article in Proceedings |
Conference | Proceedings of The 25th International Conference on Evaluation and Assessment in Software Engineering |
MU Faculty or unit | |
Citation | |
Doi | http://dx.doi.org/10.1145/3530019.3530036 |
Keywords | Software Engineering; Software Engineering Education; Software Quality; Static Code Analysis; Qualitative Analysis |
Description | Software quality sits at the core of software engineering as a discipline. Yet, although each university software-engineering and the software-development course covers software quality to some extent, practitioners still lament on graduates’ readiness for practise for this very reason—poor quality of their code. As a result, we have engaged university industrial partners in designing a master-degree Software Quality course that puts the key software quality topics in one place. In this paper, we report on the effects of the course on the quality of students’ coding projects. To this end, we have analysed a total of 54 project submissions from 27 students, with both manual and automated quality assessment methods. We have employed 30 manual and 22 automated quality characteristics related to coding style, architecture design and general development practices. In particular, we examine which characteristics of the code have improved the most and what were the most common issues. Additionally, we investigate how the code quality improvement is related to external aspects such as students’ prior coding experience, interest and their time spent on the assignments. We use the results to formulate a set of lessons learned in order to improve the design of the course and to inspire educators who consider introducing a similar type of course. |
Related projects: |