Many fields of science rely on software systems to answer different research questions. For valid results, researcher need to trust the results that scientific software produces. Consequently, quality assurance is of upmost importance. In this talk, we are investigating the impact of quality assurance in the domain of computational materials science (CMS). Based on our experience in this domain, we formulate four challenges for validation and verification for scientific software and their results: lack of precise oracles, large configuration spaces, large-scale and heterogeneous data, and global software development. Furthermore, we describe directions for future research that can potentially help on dealing with these challenges.