Computer simulations are being increasingly relied upon to inform management decisions ranging from product innovation to certification of complex, high-consequence systems. Verification and validation (V&V) are the primary means to assess the numerical and physics modeling accuracy, respectively, in computational simulation. Code verification assesses the reliability of the software coding and the numerical algorithms used in obtaining a computational solution, while solution verification addresses numerical error estimation of the computational solution for a specified set of conditions for a system of interest. Validation assesses the accuracy of a mathematical model as compared to experimentally measured response quantities. Software developers are responsible for software quality assurance and code verification of their software packages. Developers include commercial software companies, software project teams within larger organizations, and open-source software communities. This presentation will briefly discuss common practices of software quality assurance, but the focus will be on code verification procedures. The common practice in code verification testing has been to compare benchmark solutions with computational software results. Over the last three decades, the computational fluid dynamics community has shown that a more informative procedure to code verification is the determination of the observed order of numerical convergence of the discretized solution. Recommendations are made to improve the reliability of code verification testing in the future.