More Precise Yet Efficient Type Inference for Logic Programs

Vaucheret, Claudio A.; Bueno, Francisco

doi:10.1007/3-540-45789-5_10

Cited by 44 publications

(54 citation statements)

References 8 publications

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“…In a preprocessing step, the program is unfolded in order to avoid mutual recursion, which makes the analysis harder. After the unfolding step, the analysis infers types for the predicate arguments by using an existing analysis for regular types [31]. This analysis infers that for a call to a transformed version of eval/4 (with shadow variables) of the form:…”

Section: Performing the Resource Usage Analysismentioning

confidence: 99%

A Transformational Approach to Parametric Accumulated-Cost Static Profiling

Haemmerlé

López-García

Liqat

et al. 2016

Functional and Logic Programming

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Abstract. Traditional static resource analyses estimate the total resource usage of a program, without executing it. In this paper we present a novel resource analysis whose aim is instead the static profiling of accumulated cost, i.e., to discover, for selected parts of the program, an estimate or bound of the resource usage accumulated in each of those parts. Traditional resource analyses are parametric in the sense that the results can be functions on input data sizes. Our static profiling is also parametric, i.e., our accumulated cost estimates are also parameterized by input data sizes. Our proposal is based on the concept of cost centers and a program transformation that allows the static inference of functions that return bounds on these accumulated costs depending on input data sizes, for each cost center of interest. Such information is much more useful to the software developer than the traditional resource usage functions, as it allows identifying the parts of a program that should be optimized, because of their greater impact on the total cost of program executions. We also report on our implementation of the proposed technique using the CiaoPP program analysis framework, and provide some experimental results.

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Section: Performing the Resource Usage Analysismentioning

confidence: 99%

A Transformational Approach to Parametric Accumulated-Cost Static Profiling

Haemmerlé

López-García

Liqat

et al. 2016

Functional and Logic Programming

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“…The regular type arithexpression/1 is deflned in a system library and expresses that its argument is an ISO Prolog arithmetic expression [14]. However, the deflnition of the regular type rt5/l has been inferred by CiaoPP's eterms type (shape) analyzer, which is based on abstract interpretation and a regular type abstraction with widening [23].…”

Section: Type Analysis Of Chr Programsmentioning

confidence: 99%

CLP projection for constraint handling rules

Haemmerlé

López-García

Hermenegildo

2011

Proceedings of the 13th International ACM SIGPLAN Symposium on Principles and Practices of Declarative Programming

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This paper introduces and studies the notion of CLP projection for Constraint Handling Rules (CHR). The CLP projection consists of a naive translation of CHR programs into Constraint Logic Programs (CLP). We show that the CLP projection provides a safe operational and declarative approximation for CHR programs. We demónstrate moreover that a confluent CHR program has a least model, which is precisely equal to the least model of its CLP projection (closing henee a ten year-old conjecture by Abdenader et al.). Finally, we illustrate how the notion of CLP projection can be used in practice to apply CLP analyzers to CHR. In particular, we show results from applying AProVE to prove termination, and CiaoPP to infer both complexity upper bounds and types for CHR programs.

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“…It shows how the create streams program is analyzed, to obtain the program analysis graph shown in Figure 3. We use in our example well-known abstract operations for a regular type domain, in particular, the operations formalized in 44) for the eterms domain described in Example 2.2. For the analysis of library procedures, we assume that the parametric routine Atrust returns the abstract descriptions which appear in the three success assertions shown in Fig-ure 2 for the corresponding library procedures.…”

Section: An Examplementioning

confidence: 99%