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Software development plays a crucial role in driving technological advancements and fostering innovation across industries. However, the ever-increasing complexity in software systems poses significant challenges. This research aims to explore the origins of software complexity and develop strategies to mitigate it. Specifically, it investigates software complexity through the lens of Complex Problem Solving (CPS) and Software Comprehension, areas that have received limited attention thus far. The study focuses on API integration, a common area of software development, and examines two strategies (strategy A and B). These strategies incorporate the CPS techniques decomposition and Lean Thinking to address different dimensions of complexity inherent in API software. In a user study (N=30), participants had to retrieve data from an API platform and use it to build small conceptual prototype applications. Metrics related to time, successfulness in task and (perceived) effectiveness were utilized to assess the impact of the strategies on reducing interface and system complexity. The findings reveal how strategy A significantly reduces task completion times and the time required for the initial API call. Moreover, strategy A demonstrates superior performance compared to the baseline in metrics related to complexity. This highlights the effectiveness of concepts from Lean Thinking in reducing software complexity. Strategy B shows promising results in supporting developers’ individual completion of API integration tasks and facilitating software comprehension by providing tailored learning materials suitable for common-sense learners. On the whole, developers expressed high levels of satisfaction with the effectiveness of both strategies in achieving their respective goals. This research establishes a foundation for enhanced interaction with complex software systems, opening avenues for future studies to explore more effective support strategies. The outcomes contribute to

The Internet of Things (IoT) has been a rapidly expanding network in recent years and widely studied. However, many scholars focus on the technological features of the IoT network. Nevertheless, challenges still arise regarding usability and user experience (UX) of the systems in this network, especially in the consumer domain of IoT. The current study assessed those challenges by conducting a literature review. To confirm these challenges, a prestudy was conducted with ten participants that interacted with an IoT system. Results showed that the most important issues arise due to the lack of standardization amongst IoT systems, interoperability problems, the complexity of the systems, and the lack of feedback in them. Next, criteria for the design of user interfaces of IoT systems were proposed to overcome the IoT network-related challenges. These criteria were implemented in the IoT system that was used in the prestudy. To test the effect of these criteria, another study was conducted with ten participants that interacted with the system. The System Usability Scale (SUS) showed that the usability of the system had increased significantly. The AttrakDiff results demonstrated a non-significant increase of UX. Furthermore, the qualitative results of the interviews also suggested an increase in UX. The study thus offers new insights into designing user interfaces of IoT systems that are usable for consumers. Future work could replicate the study with a larger and more diverse sample size to generalize the results to a larger population. Furthermore, it would be interesting to investigate ways to standardize the development of IoT systems amongst companies developing IoT by making the suggested design criteria the norm.