Abstract
In spite of the popularity of small-step semantics, big-step semantics remain used by many researchers. However, big-step semantics suffer from a serious duplication problem, which appears as soon as the semantics account for exceptions and/or divergence. In particular, many premises need to be copy-pasted across several evaluation rules. This duplication problem, which is particularly visible when scaling up to full-blown languages, results in formal definitions growing far bigger than necessary. Moreover, it leads to unsatisfactory redundancy in proofs. In this paper, we address the problem by introducing pretty-big-step semantics. Pretty-big-step semantics preserve the spirit of big-step semantics, in the sense that terms are directly related to their results, but they eliminate the duplication associated with big-step semantics. © 2013 Springer-Verlag.
Cite
CITATION STYLE
Charguéraud, A. (2013). Pretty-big-step semantics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7792 LNCS, pp. 41–60). https://doi.org/10.1007/978-3-642-37036-6_3
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