A user is considered to be someone who would be actually using the system. The definition of a user is contextual and for any specific software project it depends on the software development methodology being developed. Satisfaction is the fulfillment of one’s wishes, expectations, needs or the pleasure that is derived from using a software product therefore “user satisfaction “is a reflection of quality from different perspective than measuring defects or code structure. Measurement in software engineering makes comparison possible and when you compare you have a choice and quality is quantified in terms of values. Therefore, this paper aims to explore the impact of software measurement scales on user satisfaction.

The multitude of services and resources available in multi-cloud environments has increased the importance of analytics applications in cloud brokering. These applications can orchestrate services and resources that reside in different domains and require inputs that a single cloud provider could not easily acquire. Yet, despite their distinct characteristics, multi-cloud analytics users have no voice in the ranking of the services in brokerage marketplaces. In this chapter, we introduce the concept and propose the implementation of explainable analytics to increase transparency and user satisfaction in multi-cloud environments. The criteria that we have identified and measured in order to summarize them in explainable results allow cloud users to acquire an understanding of the ranking rules, a crucial requirement in trustful decision-making. Our proposal accounts for a set of regulations for intelligent systems and targets their specific adaptation and use in multi-cloud environments.

This research explores the complex relationship between user-perceived Quality of Experience (QoE) and underlying network performance for multimedia traffic. As video streaming, online gaming, and interactive media dominate modern networks, ensuring consistent QoE has become a key challenge. The study develops a network performance model that integrates objective Quality of Service (QoS) parameters—such as delay, jitter, packet loss, and throughput—with subjective QoE metrics like Mean Opinion Score (MOS) and perceptual quality indices. Using simulation-based and analytical approaches, the paper evaluates how network conditions affect multimedia traffic behavior and user satisfaction. The results highlight critical thresholds for QoE degradation, enabling predictive modeling for adaptive multimedia delivery and real-time optimization. This work contributes to designing intelligent, user-centered network management systems capable of balancing resource efficiency and end-user satisfaction.