The increase in the importance of Computational Science software motivates the need to identify and understand which software engineering (SE) practices are appropriate. Because of the uniqueness of the computational science domain, exiting SE tools and techniques developed for the business/IT community are often not efficient or effective. Appropriate SE solutions must account for the salient characteristics of the computational science development environment. To identify these solutions, members of the SE community must interact with members of the computational science community. This presentation will discuss the findings from a series of case studies of CSE projects and the results of an ongoing workshop series. First, a series of case studies of computational science projects were conducted as part of the DARPA High Productivity Computing Systems (HPCS) project. The main goal of these studies was to understand how SE principles were and were not being applied in computational science along with some of the reasons why. The studies resulted in nine lessons learned about computational science software that are important to consider moving forward. Second, the Software Engineering for Computational Science and Engineering workshop brings together software engineers and computational scientists. The outcomes of this workshop series provide interesting insight into potential future trends.