Multivariate Amortised Resource Analysis for Term Rewrite Systems

We study amortised resource analysis in the context of term rewrite systems. We introduce a novel amortised analysis based on the potential method. The method is represented in an inference system akin to a type system and gives rise to polynomial bounds on the innermost runtime complexity of the analysed rewrite system. The crucial feature of the inference system is the admittance of multivariate bounds in the context of arbitrary data structures in a completely uniform way. This extends our earlier univariate resource analysis of typed term rewrite systems and continues our program of applying automated amortised resource analysis to rewriting

Work Analysis with Resource-Aware Session Types

While there exist several successful techniques for supporting programmers in deriving static resource bounds for sequential code, analyzing the resource usage of message-passing concurrent processes poses additional challenges. To meet these challenges, this article presents an analysis for statically deriving worst-case bounds on the total work performed by message-passing processes. To decompose interacting processes into components that can be analyzed in isolation, the analysis is based on novel resource-aware session types, which describe protocols and resource contracts for inter-process communication. A key innovation is that both messages and processes carry potential to share and amortize cost while communicating. To symbolically express resource usage in a setting without static data structures and intrinsic sizes, resource contracts describe bounds that are functions of interactions between processes. Resource-aware session types combine standard binary session types and type-based amortized resource analysis in a linear type system. This type system is formulated for a core session-type calculus of the language SILL and proved sound with respect to a multiset-based operational cost semantics that tracks the total number of messages that are exchanged in a system. The effectiveness of the analysis is demonstrated by analyzing standard examples from amortized analysis and the literature on session types and by a comparative performance analysis of different concurrent programs implementing the same interface.Comment: 25 pages, 2 pages of references, 11 pages of appendix, Accepted at LICS 201

TcT: Tyrolean Complexity Tool

International audienceIn this paper we present TcT v3.0, the latest version of our fully automated complexity analyser.TcT implements our framework for automated complexity analysis and focuses on extensibility and automation. TcT is open with respect to the input problem under investigation and the resource metric in question.It is the most powerful tool in the realm of automated complexity analysis of term rewrite systems. Moreover it provides an expressive problem-independent strategy language that facilitates proof search.We give insights about design choices, the implementation of the framework and report different case studies where we have applied TcT successfully

Automated Amortised Resource Analysis for Term Rewrite Systems

Based on earlier work on amortised resource analysis, we establish a novel automated amortised resource analysis for term rewrite systems. The method is presented in an inference system akin to a type system and gives rise to polynomial bounds on the innermost runtime complexity of the analysed term rewrite system. Our analysis does not restrict the input rewrite system in any way. This facilitates integration in a general framework for resource analysis of programs. In particular, we have implemented the method and integrated it into our tool TCT.(VLID)2581042Accepted versio

Bounded Expectations: Resource Analysis for Probabilistic Programs

This paper presents a new static analysis for deriving upper bounds on the expected resource consumption of probabilistic programs. The analysis is fully automatic and derives symbolic bounds that are multivariate polynomials of the inputs. The new technique combines manual state-of-the-art reasoning techniques for probabilistic programs with an effective method for automatic resource-bound analysis of deterministic programs. It can be seen as both, an extension of automatic amortized resource analysis (AARA) to probabilistic programs and an automation of manual reasoning for probabilistic programs that is based on weakest preconditions. As a result, bound inference can be reduced to off-the-shelf LP solving in many cases and automatically-derived bounds can be interactively extended with standard program logics if the automation fails. Building on existing work, the soundness of the analysis is proved with respect to an operational semantics that is based on Markov decision processes. The effectiveness of the technique is demonstrated with a prototype implementation that is used to automatically analyze 39 challenging probabilistic programs and randomized algorithms. Experimental results indicate that the derived constant factors in the bounds are very precise and even optimal for many programs

Type-Based Analysis of Logarithmic Amortised Complexity

We introduce a novel amortised resource analysis couched in a type-and-effect system. Our analysis is formulated in terms of the physicist's method of amortised analysis, and is potential-based. The type system makes use of logarithmic potential functions and is the first such system to exhibit *logarithmic amortised complexity*. With our approach we target the automated analysis of self-adjusting data structures, like splay trees, which so far have only manually been analysed in the literature. In particular, we have implemented a semi-automated prototype, which successfully analyses the zig-zig case of *splaying*, once the type annotations are fixed.Comment: 35 pages. arXiv admin note: text overlap with arXiv:1807.0824