Proceedings of the 2009 ACM SIGPLAN Workshop on ML 2009
DOI: 10.1145/1596627.1596637
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Fast and sound random generation for automated testing and benchmarking in objective Caml

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Cited by 14 publications
(13 citation statements)
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“…Boltzmann sampling is a framework for random generation of combinatorial structures (see [12] for further details). The basic idea is to give the sampler a class specification of a combinatorial structure and a value to control the size of the generated objects.…”
Section: Boltzmann Sampled Grammarsmentioning
confidence: 99%
See 1 more Smart Citation
“…Boltzmann sampling is a framework for random generation of combinatorial structures (see [12] for further details). The basic idea is to give the sampler a class specification of a combinatorial structure and a value to control the size of the generated objects.…”
Section: Boltzmann Sampled Grammarsmentioning
confidence: 99%
“…To get an efficient sampler, these two values need to be set as low as possible [12]. However, the lower these values are, the greater the likelihood of large objects being generated.…”
Section: Precisionmentioning
confidence: 99%
“…In fact, Canou and Darrasse [7] have already created a library for random test generation in OCaml based on the ideas of combinatorial species. There has also been some interesting recent work by Duregård on automatic derivation of QuickCheck generators for algebraic data types [11], and by Bernardy et al on using parametricity to improve random test generation [5]; combining these approaches with insights from the theory of species seems promising.…”
Section: Applicationsmentioning
confidence: 99%
“…Automated testing One interesting application is to use species expressions as input to a test-generator-generator, for either random [9] or exhaustive [22] testing. In fact, Canou and Darrasse [7] have already created a library for random test generation in OCaml based on the ideas of combinatorial species. There has also been some interesting recent work by Duregård on automatic derivation of QuickCheck generators for algebraic data types [11], and by Bernardy et al on using parametricity to improve random test generation [5]; combining these approaches with insights from the theory of species seems promising.…”
Section: Applicationsmentioning
confidence: 99%