The field of software development and human-computer interaction is rapidly evolving, with a focus on improving user experience, detecting biases, and enhancing code understandability. Recent research has explored the use of novel metrics, such as co-change graph entropy, to predict defects and improve software quality. Additionally, there is a growing interest in using eye tracking and gaze analysis to understand how users interact with interfaces, including carousels and low-code applications. Furthermore, researchers are developing new methods to detect biases in code reviews and improve the accessibility of software development tools. Noteworthy papers in this area include the introduction of GUSD, a genre-aware and user-specific spoiler detection framework, and the development of NRevisit, a cognitive behavioral metric for code understandability assessment. Other notable papers include the proposal of CiDiff, a diff algorithm tailored to build logs, and the creation of RecGaze, the first eye tracking and user interaction dataset for carousel interfaces.