Attaining competences in software quality oriented design based on cyclic learning - Serban, Camelia; Niculescu, Virginia; Vescan, Andreea (Proceedings - Frontiers in Education Conference, 2020)
This Research to Practice Full Paper delineates the impact of using cyclic learning to obtain competences in software quality oriented design.Nowadays, the need for quality in the software systems has become more and more a concern for many researchers and industry practitioners. Developing students' appropriate competencies and skills in writing quality programs must be an important objective of any Software Engineering related course from the Computer Science Curricula. In order to attain this goal, the paper presents a new strategy for reflecting software quality models into Software Engineering related courses based on cyclic learning. The method is based on an educational strategy that integrates the cyclic learning approach and induces to the students the awareness regarding the importance of developing quality software. We focus on a set of software quality characteristics described by the ISO25010 quality model for which we analyze the level of knowledge attained by the students during the entire bachelor cycle of studies. The study is directed by a detailed analysis of three courses: Advanced Programming Methods, Parallel and Distributed Programming, and Software Systems Verification and Validation, which were chosen in order to master the analysis complexity, but at the same time to assure coverage of as many quality attributes as possible.The investigation includes qualitative and quantitative analysis, directed by the objective of establishing the efficiency and effectiveness of the approach. The results obtained confirm both students' awareness regarding the importance of learning software quality attributes, and the efficiency of using cyclic learning in teaching this subject. We also outline several insights and advantages, and we conclude by showing that the proposed strategy fulfilled the expected objectives.