Drawing a floating-point number uniformly at random from an interval [a, b) is usually performed by a location-scale transformation of some floating-point number drawn uniformly from [0, 1). Due to the weak properties of floating-point arithmetic, such a transformation cannot ensure respect of the bounds, uniformity or spatial equidistributivity. We investigate and quantify precisely these shortcomings while reviewing the actual implementations of the method in major programming languages and libraries, and we propose a simple algorithm to avoid these shortcomings without compromising performances.