In the past decades, static analysis tools have been increasingly used in industry. However, they are also known for user-experience issues such as a high number of false positives, a lack of responsiveness, or the poor warning descriptions that they provide. To address user-experience issues in static analysis tools, we apply the user-centered design methodology. We first aim at understanding the users' motivations for using the tools, and derive design recommendations for building static analysis tools. Finally, we prototype and evaluate tools for static analysis following the recommendations. In this thesis, we focus on two groups of users: the analysis developers-who write the code of a static analysis, and the software developers-who write the code that is analyzed by an analysis tool. For both user groups, we report on developer motivations and strategies through surveys, and present concrete design recommendations for static analysis tools. We use those recommendations to build analysis tools, addressing the main user-experience issues we identify in the surveys: VisuFlow for data visualization, Cheetah for responsiveness, and Mudarri for explainability. We evaluated those tools through empirical evaluations and user studies, and showed that they allow developers to perform their tasks better than with current tools. Through this thesis, we motivate the need for more user-centered approaches for addressing decades-old user-experience issues in static analysis, putting the user at the center of the design process in order to create tools that suit their needs.