Assurance cases (ACs) have gained attention in the aerospace, medical, and other heavily-regulated industries as a means for providing structured arguments on why a product is dependable (i.e., safe, secure, etc.) for its intended application. Challenges in AC construction stem from the complexity and uniqueness of the designs, the heterogeneous nature of the required supporting evidence, and the need to assess the quality of an argument. We present an automated AC generation framework that facilitates the construction, validation, and confidence assessment of ACs based on dependability argument pat- terns and confidence patterns capturing domain knowledge. The ACs are instantiated with a system’s specification and evaluated based on the available design and verification evidence. Aerospace case studies illustrate the framework’s effectiveness, efficiency, and scalability.