Training Bachelor Students to Design Better Quality Web Apps: Preliminary Results from a Prospective Empirical Investigation

Published in Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering (EASE), 2023

Abstract: Background: There are a number of academic courses in the Bachelor Program in Computer Science (CS) on the design of Web apps. Often the internal and external quality of the developed Web apps is not adequately taken into account.
Aim: We aimed to (i) estimate the quality of Web apps developed by bachelor CS students in a Software Technologies for the Web (STW) course (a.y. 2021-22) and (ii) define a training plan (on the base of the results of the first step) for the students enrolled to this course for the a.y. 2022-23 to let them design and implement better Web apps, and (iii) experimenting the training plan by comparing the quality of Web apps developed in a.y. 2021-22 and a.y. 2022-23.
Method: We designed a prospective empirical investigation to study STW with respect to the training of bachelor students with respect to the quality (internal and external) of the developed Web apps.
Results: We observed that quality concerns are widespread in the code of the Web apps the STW students developed in the a.y. 2021-22. Therefore, we plan to ask the students of the a.y. 2022-23 to use in their development pipeline a Static Analysis Tool (SAT) to detect quality concerns in the developed Web apps and deal with them. This second step represents an ongoing stage of our research.
Conclusions: Our preliminary outcomes suggest that students must be aware that quality is of primary relevance for the development of Web apps and prepared to use SAT in the development pipeline.

Recommended citation: Sabato Nocera, Rita Francese, and Giuseppe Scanniello. 2023. Training Bachelor Students to Design Better Quality Web Apps: Preliminary Results from a Prospective Empirical Investigation. In Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering (EASE '23). Association for Computing Machinery, New York, NY, USA, 465–469. https://doi.org/10.1145/3593434.3593957
Download Paper