2018
DOI: 10.1007/s00165-018-0459-1
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Tests and proofs for custom data generators

Abstract: We address automated testing and interactive proving of properties involving complex data structures with constraints, like the ones studied in enumerative combinatorics, e.g., permutations and maps. In this paper we show testing techniques to check properties of custom data generators for these structures. We focus on random property-based testing and bounded exhaustive testing, to find counterexamples for false conjectures in the Coq proof assistant. For random testing we rely on the existing Coq plugin Quic… Show more

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Cited by 5 publications
(5 citation statements)
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“…Formally, we define Lehmer(𝑛) to be an 𝑛 + 1-element tuple, where the position 𝑘 ≀ 𝑛 stores an element of Fin k . Since the 0-th position is trivial, in practice it is ignored [Dubois and Giorgetti 2018;Vajnovszki 2011].…”
Section: Lehmer Codesmentioning
confidence: 99%
“…Formally, we define Lehmer(𝑛) to be an 𝑛 + 1-element tuple, where the position 𝑘 ≀ 𝑛 stores an element of Fin k . Since the 0-th position is trivial, in practice it is ignored [Dubois and Giorgetti 2018;Vajnovszki 2011].…”
Section: Lehmer Codesmentioning
confidence: 99%
“…3 Library of certied enumeration programs Some enumerative testing tools implement techniques such as constraint solving or local choice with backtracking, either to enumerate data or to derive eective generators from data denitions (see [15,Sect. 7] for references).…”
Section: Where Can Properties Come From?mentioning
confidence: 99%
“…Formally, we define Lehmer(𝑛) to be an 𝑛 + 1-element tuple, where the position 𝑘 ≀ 𝑛 stores an element of Fin k . Since the 0-th position is trivial, in practice it is ignored [Dubois and Giorgetti 2018;Vajnovszki 2011]. Definition 5.15 (Lehmer : N → U).…”
Section: Lehmer Codesmentioning
confidence: 99%