Cost Recurrences for DML Programs

Grobauer, Bernd

doi:10.7146/brics.v8i25.21685

Cited by 22 publications

(25 citation statements)

References 8 publications

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“…A significant additional improvement brought about by [28] is that it is combined with a sized types abstract domain, which allows the inference of non-trivial cost bounds when they depend on the sizes of input terms and their subterms at any position and depth. Recently, many other approaches have been proposed for resource analysis [30,12,9,13,23,8,1,2]. While based on different techniques, all these analyses infer, for all predicates p of a given program P, an approximation of the notion of cost that we call the standard cost or single call cost.…”

Section: The Classical Cost Relations-based Parametric Static 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: The Classical Cost Relations-based Parametric Static 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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“…Other resource analyses that can in principle obtain polynomial bounds are approaches based on recurrences pioneered by Grobauer [9] and Flajolet [10]. In those systems, an a priori unknown resource bounding function is introduced for each function in the code; by a straightforward intraprocedural analysis a set of recurrence equations or inequations for these functions is then derived.…”

Section: Conclusion and Related Workmentioning

confidence: 99%

Amortized Resource Analysis with Polynomial Potential

Hoffmann

Hofmann

2010

Programming Languages and Systems

108

128

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Abstract. In 2003, Hofmann and Jost introduced a type system that uses a potential-based amortized analysis to infer bounds on the resource consumption of (first-order) functional programs. This analysis has been successfully applied to many standard algorithms but is limited to bounds that are linear in the size of the input.Here we extend this system to polynomial resource bounds. An automatic amortized analysis is used to infer these bounds for functional programs without further annotations if a maximal degree for the bounding polynomials is given. The analysis is generic in the resource and can obtain good bounds on heap-space, stack-space and time usage.

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“…The importance of providing user information to direct and make tractable automatic techniques has long been recognized in the areas such as theorem proving [10], and is beginning to be recognized in the area of program analysis as well [14,25].…”

Section: Annotations Used In Other Kinds Of Automated Toolsmentioning

confidence: 99%

“…PEPM '02, Jan. [14][15]2002 to programmer-supplied invariants. A partial evaluator simplifies static computations, which depend only on information that can be inferred from the invariants and the program structure, and reconstructs the remaining dynamic computations to form the specialized program.…”

Section: Introductionmentioning

confidence: 99%

Towards bridging the gap between programming languages and partial evaluation

Meur

Lawall

Consel

2002

Proceedings of the 2002 ACM SIGPLAN Workshop on Partial Evaluation and Semantics-Based Program Manipulation

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Partial evaluation is a program-transformation technique that automatically specializes a program with respect to user-supplied invariants. Despite successful applications in areas such as graphics, operating systems, and software engineering, partial evaluators have yet to achieve widespread use. One reason is the difficulty of adequately describing specialization opportunities. Indeed, under-specialization or over-specialization often occurs, without any direct feedback to the user as to the source of the problem.We have developed a high-level, module-based language allowing the programmer to guide the choice of both the code to specialize and the invariants to exploit during the specialization process. To ease the use of partial evaluation, the syntax of this language is similar to the declaration syntax of the target language of the partial evaluator. To provide feedback to the programmer, declarations are checked throughout the analyses performed by partial evaluation. The language has been successfully used by a signal-processing expert in the design of a specializable Forward Error Correction component.

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Cost Recurrences for DML Programs

Cited by 22 publications

References 8 publications

A Transformational Approach to Parametric Accumulated-Cost Static Profiling

A Transformational Approach to Parametric Accumulated-Cost Static Profiling

Amortized Resource Analysis with Polynomial Potential

Towards bridging the gap between programming languages and partial evaluation

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