Data and software are the foundation for a vast variety and volume of scientific research. Computational research is used in most scientific disciplines to make sense of small or huge datasets using everything from one-off scripts to high-performance computing infrastructures. At some point, all these works are presented to a scientific community and in the current academic reality, the publication of a research paper is a crucial step for the recognition of research outputs and career advancement. Research papers are increasingly accompanied by data and software to ensure transparency, reproducibility, and reusability. This change is driven by shifting community practice as well as by publisher guidelines. However, the actual inspection of these building blocks is not a common part of the publication and peer review process. The CODECHECK initiative tries to make code execution standard practice in peer review. A CODECHECK has a particular focus and underlies a set of principles, which will be introduced in this talk. We also present the implementation options for CODECHECK and highlight the possibilities for research software engineers to participate in academic peer review as codecheckers. CODECHECK demonstrates how good scientific and development practices can be spread, encouraged, and potentially enforced through communication and collaboration - especially if powered by RSEng expertise.