We survey several commonly-used quasi-Newton methods and line-search algorithms for unconstrained and box-constrained optimization and consider their underlying strategies. By taking advantage of an implicit similarity in two existing algorithms, we develop a method for box-constrained optimization that includes a new way to compute a search direction and a new line-search algorithm. On a collection of standardized problems, this method is over $35\%$ faster than the leading comparable alternative.