A general framework for static profiling of parametric resource usage

López-García, Pedro; Klemen, Maximiliano; Liqat, Umer; Hermenegildo, Manuel V.

doi:10.1017/s1471068416000442

Cited by 11 publications

(8 citation statements)

References 28 publications

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“…These include abstract interpreters for a variety of domains including non-functional program properties such as complexity and resource usage, e.g. [29]. Big-step based interpretation using Horn clause interpreters was proposed by Kahn and others [22,6,7] but not as a basis for translation.…”

Section: Discussionmentioning

confidence: 99%

From Big-Step to Small-Step Semantics and Back with Interpreter Specialisation

Gallagher

Hermenegildo

Kafle

et al. 2020

Electron. Proc. Theor. Comput. Sci.

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We investigate representations of imperative programs as constrained Horn clauses. Starting from operational semantics transition rules, we proceed by writing interpreters as constrained Horn clause programs directly encoding the rules. We then specialise an interpreter with respect to a given source program to achieve a compilation of the source language to Horn clauses (an instance of the first Futamura projection). The process is described in detail for an interpreter for a subset of C, directly encoding the rules of big-step operational semantics for C. A similar translation based on small-step semantics could be carried out, but we show an approach to obtaining a small-step representation using a linear interpreter for big-step Horn clauses. This interpreter is again specialised to achieve the translation from big-step to small-step style. The linear small-step program can be transformed back to a big-step non-linear program using a third interpreter. A regular path expression is computed for the linear program using Tarjan's algorithm, and this regular expression then guides an interpreter to compute a program path. The transformation is realised by specialisation of the path interpreter. In all of the transformation phases, we use an established partial evaluator and exploit standard logic program transformation to remove redundant data structures and arguments in predicates and rename predicates to make clear their link to statements in the original source program.

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Section: Discussionmentioning

confidence: 99%

From Big-Step to Small-Step Semantics and Back with Interpreter Specialisation

Gallagher

Hermenegildo

Kafle

et al. 2020

Electron. Proc. Theor. Comput. Sci.

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“…They are often the first choice for web programming, prototyping, and scripting. The lack of inherent mechanisms for ensuring program data manipulation correctness (e.g., via full static typing or other forms of full static built-in verification) has sparked the evolution of flexible solutions, including assertion-based approaches (Bueno et al Our proposal is to use static cost analysis (Debray et al 1990;Debray and Lin 1993;Debray et al 1997;Portillo et al 2002;Albert et al 2012;Serrano et al 2014;Lopez-Garcia et al 2016) instead of (or as a complement to) dynamic profiling. Such analysis is aimed at inferring statically safe upper and lower bounds on execution costs, i.e., bounds that are guaranteed and will never be violated in actual executions.…”

Section: Introductionmentioning

confidence: 99%

“…Our proposal is to use static cost analysis (Debray et al 1990;Debray and Lin 1993;Debray et al 1997;Portillo et al 2002;Albert et al 2012;Serrano et al 2014;Lopez-Garcia et al 2016) instead of (or as a complement to) dynamic profiling. Such analysis is aimed at inferring statically safe upper and lower bounds on execution costs, i.e., bounds that are guaranteed and will never be violated in actual executions.…”

mentioning

confidence: 99%

Static Performance Guarantees for Programs with Runtime Checks

Klemen

Stulova

López-García

et al. 2018

Proceedings of the 20th International Symposium on Principles and Practice of Declarative Programming

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Instrumenting programs for performing run-time checking of properties, such as regular shapes, is a common and useful technique that helps programmers detect incorrect program behaviors. This is specially true in dynamic languages such as Prolog. However, such run-time checks inevitably introduce run-time overhead (in execution time, memory, energy, etc.). Several approaches have been proposed for reducing such overhead, such as eliminating the checks that can statically be proved to always succeed, and/or optimizing the way in which the (remaining) checks are performed. However, there are cases in which it is not possible to remove all checks statically (e.g., open libraries which must check their interfaces, complex properties, unknown code, etc.) and in which, even after optimizations, these remaining checks still may introduce an unacceptable level of overhead. It is thus important for programmers to be able to determine the additional cost due to the run-time checks and compare it to some notion of admissible cost. The common practice used for estimating run-time checking overhead is profiling, which is not exhaustive by nature. Instead, we propose a method that uses static analysis to estimate such overhead, with the advantage that the estimations are functions parameterized by input data sizes. Unlike profiling, this approach can provide guarantees for all possible execution traces, and allows assessing how the overhead grows as the size of the input grows. Our method also extends an existing assertion verification framework to express "admissible" overheads, and statically and automatically checks whether the instrumented program conforms with such specifications. Finally, we present an experimental evaluation of our approach that suggests that our method is feasible and promising.

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“…While our previous approach could conceivably be extended to deal with such programs, it would certainly result in a more complicated and indirect solution. The results of this activity have been published in [78].…”

Section: Contributionsmentioning

confidence: 99%

“…We provide the formalization of the method and present also results from its implementation and experimental evaluation. As already said, our proposal builds on static cost analysis [8,27,29,31,78,104,117] instead of (or as a complement to) dynamic profiling. This type of analysis is aimed at inferring statically (i.e., without actually running the program with concrete data) safe upper and lower bounds on execution costs, i.e., bounds that are guaranteed and will never be violated in actual executions.…”

Section: Introductionmentioning

confidence: 99%

A General Framework for Static Resource Analysis and Profiling of (Parallel) Programs and an Application to Runtime Checking

Klemen¹

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I would also like to give special thanks to Manuel Hermenegildo for his humility, selfless support and constant advice, and for transmitting his passion and enthusiasm in every talk and meeting.My sincere thanks also to John Gallagher, for welcoming me so generously and kindly as a visiting student in Roskilde, Denmark. It was an unforgettable experience to work with him in such beautiful land. I have acquired very valuable knowledge, useful both for my thesis and my life (for example, the importance of hygge).I would also like to thank Miguel Ángel Perpiñán, for generously sharing all his knowledge and expertise, which have been fundamental for the completion of this dissertation.I would like to express my gratitude to the IMDEA Software Institute, its former Director Manuel Hermenegildo and its current Director Manuel Carro, for funding my Ph.D. and providing me with such inspiring workplace. Thanks to the support staff for their permanent help and attention in every detail. Also, thanks to all the researchers, it has been the most amazing experience to share a work environment with some of the world top researchers in their respective fields.Many thanks to all my office mates and members of the CLIP group, both past and present, for encouraging me, listening to me, sharing their ideas and enduring my anxiety when deadlines were close:

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A general framework for static profiling of parametric resource usage

Cited by 11 publications

References 28 publications

From Big-Step to Small-Step Semantics and Back with Interpreter Specialisation

From Big-Step to Small-Step Semantics and Back with Interpreter Specialisation

Static Performance Guarantees for Programs with Runtime Checks

A General Framework for Static Resource Analysis and Profiling of (Parallel) Programs and an Application to Runtime Checking

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