Minhas, N. M., Koppula, T., Petersen, K., & Börstler, J. (2023). Using goal—question—metric to compare research and practice perspectives on regression testing. Journal of Software: Evolution and Process, 35, e2506.
Petersen, K., Wasse, A., Cruse, T., Sietas, J., & Gerken, J. M. (2023). On the Impact of a Business Intelligence System on Analysis Effort: A Case Study of Flensburg Municipality in Germany. Anwendungen und Konzepte der Wirtschaftsinformatik (AKWI), (18), 13.
Börstler, J., Bin Ali, N., Svensson, M., & Petersen, K. (2023). Investigating acceptance behavior in software engineering—theoretical perspectives. Journal of Systems and Software, 198, 111592.
Börstler, J., Bin Ali, N., & Petersen, K. (2023). Double-counting in software engineering tertiary studies—An overlooked threat to validity. Information and Software Technology, 107174.
Minhas, N. M., Irshad, M., Petersen, K., & Börstler, J. (2023). Lessons learned from replicating a study on information-retrieval-based test case prioritization. Software quality journal, 1–33.
Irshad, M., Börstler, J., & Petersen, K. (2022). Supporting refactoring of BDD specifications—An empirical study. Information and Software Technology, 141, 106717.
Lübben, R., & Misfeld, N. (2022). Exploring the Measurement Lab Open Dataset for Internet Performance Evaluation: The German Internet Landscape. Electronics, 11. http://doi.org/10.3390/electronics11010162
Abstract
The Measurement Lab (MLab) provides a large and open collection of Internet performance measurements. We make use of it to look at the state of the German Internet by a structured analysis, in which we carve out expressive results from the dataset to identify busy hours and days, the impact of server locations and congestion control protocols, and compare Internet service providers. Moreover, we examine the impact of the COVID-19 lockdown in Germany. We observe that only parts of the Internet show a performance degradation at the beginning of the lockdown and that a large impact in performance depends on the network the servers are located in. Furthermore, the evolution of congestion control algorithms is reflected by performance improvements. For our analysis, we focus on the busy hours. From the end-user perspective, this time is of most interest to identify if the network can support challenging services such as video streaming or cloud gaming at these intervals.