Efficient and accurate sensitivity analysis is essential to the success of gradient-based optimization, especially for large-scale applications that require substantial computational effort for function evaluations. We discussed three major approaches for sensitivity analysis—the brute-force finite difference, discrete, and continuum methods. We pointed out the pros and cons of individual approaches. In practical implementation, the semianalytical and continuum-discrete methods are general and efficient. In addition, considering accuracy, the continuum-discrete method is, in our opinion, the best approach for support of DSA in general and large-scale structural problems. However, it requires a more in-depth study for the reader to become proficient in implementing the method and integrating it with commercial FEA software. We hope the discussions provided in this chapter offer a gateway for those who intend to get into a more in-depth study in the sensitivity analysis area. We also briefly discussed topology optimization, which has gained lots of attention in recent years in support of structural layout design. For those who are interested in pursuing graduate study, topology optimization and relevant subjects can be an interesting thesis topic. In addition, research in studying mechanics at the atomistic level, using techniques such as MD or the bridging scale method presented in the second case study, also provides viable topics for further research.