PrologCheck – Property-Based Testing in Prolog

Amaral, Cláudio do Prado; Florido, Mário; Costa, Vítor Santos

doi:10.1007/978-3-319-07151-0_1

Cited by 15 publications

(30 citation statements)

References 19 publications

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“…Example 2. The following example shows the definition of a non-deterministic list insertion operation in Curry: Thus, perm [1,2,3,4] non-deterministically evaluates to all 24 permutations of the input list.…”

Section: Functional Logic Programming and Currymentioning

confidence: 99%

“…For instance, suppose we want to compute the minimum of a list by returning the head element of the sorted list: Then head (sort [3,2,1]) returns 1, as expected, but head (sort' [3,2,1]) returns 1 as well as 2. The latter unintended value is obtained by computing the permutation [2,3,1] so that head (idSorted [2,3,1]) returns 2, since the call to idSorted [3,1] is not evaluated due to non-strictness.…”

Section: Functional Logic Programming and Currymentioning

confidence: 99%

“…But they compute different partial values for some input. For example, sort' [2,3,1] * → 2:⊥ whereas sort [2,3,1] cannot be derived to 2:⊥. If we limit our consideration to result values only, we could not determine that sort and sort' are not equivalent.…”

Section: Refined Equivalence Criteriamentioning

confidence: 99%

“…The former is more laborious since an expression might evaluate to many partial values even if it has a single value. For instance, consider the list generator: The expression fromTo 1 5 evaluates to the single value [1,2,3,4,5]. According to the reduction relation defined in Sect.…”

Section: Refined Equivalence Criteriamentioning

confidence: 99%

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Equivalence Checking of Non-deterministic Operations

Antoy

Hanus²

2018

Functional and Logic Programming

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Checking the semantic equivalence of operations is an important task in software development. For instance, regression testing is a routine task performed when software systems are developed and improved, and software package managers require the equivalence of operations in different versions of a package within the same major number version. A solid foundation is required to support a good automation of this process. It has been shown that the notion of equivalence is not obvious when non-deterministic features are present. In this paper, we discuss a general notion of equivalence in functional logic programs and develop a practical method to check it. Our method is integrated in a property-based testing tool which is used in a software package manager to check the semantic versioning of software packages. MotivationFunctional logic languages combine the most important features of functional and logic programming in a single language (see [4,20] for recent surveys). In this paper we consider Curry [24], a contemporary functional logic language that conceptually extends Haskell with common features of logic programming. Hence, a Curry function is evaluated lazily and may be non-deterministic when defined by overlapping rules. As discussed in [7], the combination of these features raises new issues for defining the equivalence of expressions. Actually, three different notions of equivalence can be distinguished:1. Ground equivalence: Two expressions are equivalent if they produce the same results when their variables are replaced by ground terms. 2. Computed-result equivalence: Two expressions are equivalent if they produce the same outcomes, i.e., variables in expressions are considered as free variables which might be instantiated during the evaluation process. 3. Contextual equivalence: Two expressions are equivalent if they produce the same outcomes in all possible contexts.⋆ This is an extended version of a paper appeared in → denotes the reflexive and transitive closure of this reduction relation. The equivalence of this rewrite relation and CRWL is shown in [28]. Equivalent OperationsAs discussed above, equivalence of operations can be defined in different ways. Ground equivalence and computed result equivalence only compare the values of applications. This is too weak since some operations have no finite values.Example 3. Consider the following operations that generate infinite lists of numbers: ints1 n = n : ints1 (n+1) ints2 n = n : ints2 (n+2)Lemma 2. Let x be an integer and rs and xs lists of integers such that x ≤ z for all z ∈ rs. Then, for some list of integers r, minRest x rs xs * → (m, r) with m ≤ z for all z ∈ (x : rs++xs) and perm (x : rs++xs) * → m : r (where rs++xs denotes the concatenation of the lists rs and xs).Proof. We assume that x ≤ z for all z ∈ rs. We prove the lemma by induction on the length of the list xs.Base case: xs = []:Since minRest x rs [] *

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Section: Functional Logic Programming and Currymentioning

confidence: 99%

Section: Functional Logic Programming and Currymentioning

confidence: 99%

Section: Refined Equivalence Criteriamentioning

confidence: 99%

Section: Refined Equivalence Criteriamentioning

confidence: 99%

See 2 more Smart Citations

Equivalence Checking of Non-deterministic Operations

Antoy

Hanus²

2018

Functional and Logic Programming

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“…Both issues are tricky, linked as they are to the well known problem of the quality of test coverage. There are at least two versions of QuickCheck for Prolog, see https://github.com/mndrix/quickcheck and (Amaral et al 2014). Both essentially implement the NAF approach and struggle with types.…”

Section: Testing Model Checking and Mechanized Metatheorymentioning

confidence: 99%

αCheck: A mechanized metatheory model checker

Cheney¹,

Momigliano²

2017

Theory and Practice of Logic Programming

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The problem of mechanically formalizing and proving metatheoretic properties of programming language calculi, type systems, operational semantics, and related formal systems has received considerable attention recently. However, the dual problem of searching for errors in such formalizations has attracted comparatively little attention. In this article, we present αCheck, a bounded model-checker for metatheoretic properties of formal systems specified using nominal logic. In contrast to the current state of the art for metatheory verification, our approach is fully automatic, does not require expertise in theorem proving on the part of the user, and produces counterexamples in the case that a flaw is detected. We present two implementations of this technique, one based on negation-as-failure and one based on negation elimination, along with experimental results showing that these techniques are fast enough to be used interactively to debug systems as they are developed. Under consideration for publication in Theory and Practice of Logic Programming (TPLP)

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Concolic Testing of Functional Logic Programs

Tikovsky¹

2018

Declarative Programming and Knowledge Management

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PrologCheck – Property-Based Testing in Prolog

Cited by 15 publications

References 19 publications

Equivalence Checking of Non-deterministic Operations

Equivalence Checking of Non-deterministic Operations

αCheck: A mechanized metatheory model checker

Concolic Testing of Functional Logic Programs

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