The research landscape in the field of software energy efficiency and performance optimization is witnessing significant advancements, particularly in the context of emerging technologies like Software-Defined Vehicles (SDVs) and AI-driven systems. A notable trend is the adoption of containerization and virtualization techniques to streamline software development and updates, with evaluations demonstrating their feasibility and minimal performance impact on real-world applications. Additionally, methodologies for fine-grain GPU power visibility are being developed to address the escalating power demands of AI computations, offering insights into power variation and optimization strategies. Tools like CPPJoules are filling critical gaps in energy measurement for foundational programming languages such as C++, enabling developers to assess and improve energy efficiency in a broader range of applications. Furthermore, studies on the energy consumption of programming solutions highlight the correlation between execution speed and energy efficiency, providing valuable insights for optimizing software performance with sustainability in mind. These developments collectively push the boundaries of energy-aware computing, fostering more efficient and sustainable software systems.