A modular and generic analysis server system for functional logic programs

Hanus, Michael; Skrlac, Fabian

doi:10.1145/2543728.2543744

Cited by 9 publications

(5 citation statements)

References 30 publications

(50 reference statements)

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“…3. To implement the analysis, we used the Curry analysis system CASS [20]. CASS is a generic program analysis system which provides an infrastructure to implement new bottom-up analyses.…”

Section: Methodsmentioning

confidence: 99%

“…Since Curry with all its syntactic sugar (we have only presented a small fragment of it) is a quite rich source language, a simpler intermediate representation of Curry programs has been shown to be useful to describe the operational semantics [1], compile programs [10,19], or implement analyzers [20] and similar tools. Programs of this intermediate language, called FlatCurry, contain a single rule for each function where the pattern matching strategy is represented by case expressions.…”

Section: Functional Logic Programming and Currymentioning

confidence: 99%

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From Boolean Equalities to Constraints

Antoy

Hanus

2015

Logic-Based Program Synthesis and Transformation

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Abstract. Although functional as well as logic languages use equality to discriminate between logically different cases, the operational meaning of equality is different in such languages. Functional languages reduce equational expressions to their Boolean values, True or False, logic languages use unification to check the validity only and fail otherwise. Consequently, the language Curry, which amalgamates functional and logic programming features, offers two kinds of equational expressions so that the programmer has to distinguish between these uses. We show that this distinction can be avoided by providing an analysis and transformation method that automatically selects the appropriate operation. Without this distinction in source programs, the language design can be simplified and the execution of programs can be optimized. As a consequence, we show that one kind of equational expressions is sufficient and unification is nothing else than an optimization of Boolean equality. MotivationFunctional as well as logic programming languages are based on the common idea to specify computational problems in a high-level and descriptive manner. However, the computational entities and, thus, the programming styles are different. This can be seen in a prominent feature of such languages: the discrimination between logically different cases of a given problem. Functional (as well as imperative) languages use Boolean equations for this purpose, i.e., an equational expression is reduced to either True or False and, depending on the computed result, a different computation path is selected. A typical example is the factorial function where the base case is distinguished from the recursive case by comparing the argument with 0: 1 fac n = if n==0 then 1 else n * fac (n-1) The equality symbol "=" used in this program is different from the Boolean equality "==" above. For instance, in the first rule it is not intended to evaluate X=[] to True or False, but this equality must hold to proceed with this rule, i.e., it is a constraint for subsequent evaluation steps. As a consequence, it is not necessary to fully evaluate equational expressions but one can continue a computation even with partial knowledge, as long as the constraint is ensured to hold. For instance, if we want to ensure that a list L ends with the element 0, we can write Functional logic languages attempt to combine the most important features of functional and logic programming in a single language (see [5,18] for recent surveys). In particular, the functional logic language Curry [21] extends Haskell by common features of logic programming, i.e., non-determinism, free variables, and equational constraints. Due to its roots in functional and logic programming, Curry provides two kinds of equalities: Boolean equality ("==") as in functional programming and equational constraints ("=:=") as in logic programming. The motivation for this decision is to support nested case distinctions, like in functional programming, as well as rule-oriented programming with partial i...

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“…3. To implement the analysis, we used the Curry analysis system CASS [20]. CASS is a generic program analysis system which provides an infrastructure to implement new bottom-up analyses.…”

Section: Methodsmentioning

confidence: 99%

Section: Functional Logic Programming and Currymentioning

confidence: 99%

From Boolean Equalities to Constraints

Antoy

Hanus

2015

Logic-Based Program Synthesis and Transformation

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“…These applications include implementing Curry by compiling into other languages, like Prolog [17] or Haskell [10]. FlatCurry is also the basis for specifying the operational semantics of Curry programs [1], building generic analysis tools [18], or verifying properties of Curry programs [15,16]. The FlatCurry format of a Curry program removes some syntactic constructs, such as nested scopes and infix notation, that make source programs more human readable.…”

Section: Flatcurrymentioning

confidence: 99%

ICurry

Antoy,

Hanus,

Jost

et al. 2019

Preprint

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FlatCurry is a well-established intermediate representation of Curry programs used in compilers that translate Curry code into Prolog and Haskell code. Some FlatCurry constructs have no direct translation into imperative code. These constructs must be each handled differently when translating Curry code into C, C ++ and Python code. We introduce a new representation of Curry programs, called ICurry, and derive a translation from all FlatCurry constructs into ICurry. We present the syntax of ICurry and the translation from FlatCurry to ICurry. We present a model of functional logic computations as graph rewriting, show how this model can be implemented in a low-level imperative language, and describe the translation from ICurry to this model.

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“…In order to decide between these transformation options, our extension of CurryCheck uses the analysis framework CASS [23] to approximate the termination behavior of both operations. If the termination property of both operations can be proved (for this purpose, CASS uses an ordering on arguments in recursive calls), the second transformation is used, otherwise the first one is.…”

Section: Using Termination Informationmentioning

confidence: 99%

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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A modular and generic analysis server system for functional logic programs

Cited by 9 publications

References 30 publications

From Boolean Equalities to Constraints

From Boolean Equalities to Constraints

ICurry

Equivalence Checking of Non-deterministic Operations

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