The problem of propositional satisfiability (SAT) has found a number of applications in both theoretical and practical computer science. In many applications, however, knowing a formula's satisfiability alone is insufficient. Often, some other properties of the formula need to be computed. This article focuses on one such property: the backbone of a formula, which is the set of literals that are true in all the formula's models. Backbones find theoretical applications in characterization of SAT problems and they also find practical applications in product configuration or fault localization. This article overviews existing algorithms for backbone computation and introduces two novel ones. Further, an extensive evaluation of the algorithms is presented. This evaluation demonstrates that one of the novel algorithms significantly outperforms the existing ones.