Software

Our goal is to generate restructuring recommendations for research software systems based on software architecture descriptions that were obtained via reverse engineering. We reconstructed these software architectures via static and dynamic analysis methods in the reverse engineering process. To do this, we combined static and dynamic analysis for call relationships and dataflow into a hierarchy of six analysis methods. For generating optimal restructuring recommendations, we use genetic algorithms, which optimize the module structure. For optimizing the modularization, we use coupling and cohesion metrics as fitness functions. We applied these methods to Earth System Models to test their efficacy. In general, our results confirm the applicability of genetic algorithms for optimizing the module structure of research software. Our experiments show that the analysis methods have a significant impact on the optimization results. A specific observation from our experiments is that the pure dynamic analysis produces significantly better modularizations than the optimizations based on the other analysis methods that we used for reverse engineering. Furthermore, a guided, interactive optimization with a domain expert’s feedback improves the modularization recommendations considerably. For instance, cohesion is improved by 57% with guided optimization.

To ensure adequate skill development, but also competitive advantage as a software engineering organization, initiatives in cybersecurity training is one of several important investment decisions to make for management. This study builds upon three case organizations in Sweden and Greece, where managers’ and software developers’ perceptions on trialability and observability effects are analyzed, grounded in the theory of innovation diffusion. Using interviews and a developer-centric survey, both quantitative and qualitative data are collected, and used in combination to support the development of a pre-investment framework for management. The analysis includes thematic analysis, cosine similarity comparison, and, to some extent, sentiment polarity scoring. A pre-investment framework consisting of a process of seven concrete steps is proposed, based on the empirical findings in the study.

This study investigates how Development and Operations (DevOps) practices impact Project Management Office (PMO) governance within the technology sector of the United Arab Emirates (UAE). It addresses the need for agile-aligned governance frameworks by exploring how DevOps principles affect traditional PMO structures. A quantitative cross-sectional survey was conducted, and data was collected from 321 DevOps and PMO professionals in UAE organizations. The analysis, using Partial Least Squares Structural Equation Modelling (PLS-SEM), revealed a moderate positive correlation between specific DevOps practices—such as microservices, Minimum Viable Experience (MVE) culture, continuous value streams, automated configuration, and continuous delivery—and effective PMO governance. The study’s novel theoretical contribution is the integration of the Dynamic Capabilities Framework (DCF) with the Agile DevOps Reference Model (ADRM) to examine this alignment, bridging strategic agility and operational execution. This research offers actionable insights for UAE organizations and policymakers seeking to enhance governance and digital maturity.