A Systematic Analysis of Higher Education on Software Engineering in the Netherlands (Online Appendix)

This is the online appendix of the paper "A Systematic Analysis of Higher Education on Software Engineering in the Netherlands". The appendix includes materials that promote transparency, verifiability, and replication. course_descriptions.zip: course descriptions, taken from the educational catalogs, for the analyzed courses; wordclouds.zip: Python code (Jupyter notebook) that we used to generate the wordclouds, including the input course descriptions; agreement-round1.xlsx and agreement-round2.xlsx: Excel files that document the changes that underwent in our coding in Phase 5 and Phase 6 of our research method (see Figure 1 in the paper); courselist-MASTER.xlsx: the list of courses that are part of the analysis, including their coding. The Excel file consists of multiple tabs: Matrix: the final list of the 207 included courses, including their final coding; Matrix removed: the list of 109 courses that were provided by the participants in our study but that we excluded from our analysis; Notes: some comments on the coding scheme; Categories: the guidelines we employed as a tool to assist us in determining whether a course description would fit a certain KA/category; Counting: aggregate sums/values from Matrix, which shows the frequency of KAs; Plots: some charts that reflect our data, used to explore the results; course_spider.py: the script we used to retrieve the course descriptions from the syllabi on the universities' pages; this script led to the contents of course_descriptions.zip; freq_versen.xlsx: an Excel file that includes the outputs of the most frequent words in the course descriptions, used in Table 2 and Table 3 in the paper; heatmap_courses.py: Python script that first calculates Spearman correlations between knowledge areas, starting from the courselist-MASTER.xlsx file, and then generates the heatmap visualization in Figure 4 of the paper; heatmap_kas_unis.py: Python script that generates the heatmap visualization in Figure 5 of the paper; uni_topic_recurrence.py: Python script that takes a CSV version of the courses and then generates the distribution of courses mapped to knowledge areas, organized by universities, shown in Figure 5 of the paper. This work complements the following paper: Bastiaan Heeren, Fabiano Dalpiaz, Mazyar Seraj, Roberto Verdecchia and Vadim Zaytsev. A Systematic Analysis of Higher Education on Software Engineering in the Netherlands. Accepted for publication in the Journal of Systems and Software, 2026.