Next-generation software development competencies: Identification of technical and non-technical skills needed by modern industry
Öz
Anahtar Kelimeler
Competency analysis, Skill requirements, Software development skills, Topic modeling
Kaynakça
- Aken, A., Litecky, C., Ahmad, A., & Nelson, J. (2010). Mining for computing jobs. IEEE Software, 27(1), 78–85.
- Barua, A., Thomas, S. W., & Hassan, A. E. (2014). What are developers talking about? An analysis of topics and trends in Stack Overflow. Empirical Software Engineering. https://doi.org/10.1007/s10664-012-9231-y
- Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77–84.
- Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3(4–5), 993–1022. https://doi.org/10.1017/9781009218245.012
- Burkhardt, S., & Kramer, S. (2019). Decoupling sparsity and smoothness in the dirichlet variational autoencoder topic model. Journal of Machine Learning Research, 20.
- Chen, T. H., Thomas, S. W., & Hassan, A. E. (2016). A survey on the use of topic models when mining software repositories. Empirical Software Engineering, 21(5), 1843–1919. https://doi.org/10.1007/s10664-015-9402-8
- De Mauro, A., Greco, M., Grimaldi, M., & Ritala, P. (2018). Human resources for Big Data professions: A systematic classification of job roles and required skill sets. Information Processing and Management, 54(5), 807–817. https://doi.org/10.1016/j.ipm.2017.05.004
- Debortoli, S., Müller, O., & Vom Brocke, J. (2014). Comparing business intelligence and big data skills: A text mining study using job advertisements. Business and Information Systems Engineering, 6(5), 289–300. https://doi.org/10.1007/s12599-014-0344-2
- Egger, R., & Yu, J. (2022). A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts. Frontiers in Sociology, 7. https://doi.org/10.3389/fsoc.2022.886498
- Feng, J., Zhang, Z., Ding, C., Rao, Y., Xie, H., & Wang, F. L. (2022). Context reinforced neural topic modeling over short texts. Information Sciences, 607, 79–91. https://doi.org/10.1016/j.ins.2022.05.098