In the present letter, we have examined the different algorithmic elements that were conceived and applied in the recently suggested ''2DSA'' size-and-shape distribution by Brookes et al. (2009) . We have compared this with the standard approach that is well established for solving illposed integral equations problems in many fields, which rests on well-established linear algebra and related numerical tools of linear least-squares analysis. Contrary to the assertion of Brookes, Cao, and Demeler, the application of the standard approach to the size-and-shape distribution problem is quite feasible on ordinary laboratory computers within only a few minutes of computation time, even when using high-resolution grids suitable to fully extract the experimental information content. As implemented in SEDFIT, this approach is being applied in many laboratories (Markossian et al. 2006; Chang et al. 2007; Deng et al. 2007; Race et al. 2007; Broomell et al. 2008; Brown et al. 2008; Chebotareva et al. 2008; Iseli et al. 2008; Moncrieffe et al. 2008; Paz et al. 2008; Sivakolundu et al. 2008; Wang et al. 2008; Eronina et al. 2009; Mortuza et al. 2009 ). Since this can supply exact (up to numerical precision) best-fit solutions, we have applied it to a data analysis example to serve as a reference solution in a study of the performance of different computational strategies on which 2DSA relies. This illustrates the consequences of the deviations from the established mathematical reference frame that should be expected to arise in Demeler's 2DSA approach.