Automated synthesis of systems that are correct by construction has been a long-standing goal of computer science. Synthesis is a creative task and requires human intuition and skill. Its complete automation is currently beyond the capacity of programs that do automated reasoning. However, there is a pressing need for tools and techniques that can automate non-intuitive and error-prone synthesis tasks. This thesis proposes a novel synthesis approach to solve such tasks in the synthesis of programs as well as the synthesis of switching logic for cyber-physical systems. The common underlying theme of the proposed synthesis techniques is a novel combination of deductive reasoning, inductive reasoning and structure hypotheses on the system under synthesis. We call this reasoning technique SCIDUCTION that stands for 'Structurally Constrained Induction and Deduction'. SCIDUCTION constrains inductive and deductive reasoning using structure hypotheses, and actively combines inductive and deductive reasoning: for instance, deductive techniques generate examples for learning, and inductive techniques generate generalizations as candidate designs to be proved or disproved by deduction.