Klaus Aehlig

Bio: Klaus Aehlig is an academic researcher from Ludwig Maximilian University of Munich. The author has contributed to research in topics: Lambda calculus & Normalization (statistics). The author has an hindex of 11, co-authored 22 publications receiving 644 citations. Previous affiliations of Klaus Aehlig include University of Toronto.

Multivariate amortized resource analysis

Abstract: We study the problem of automatically analyzing the worst-case resource usage of procedures with several arguments. Existing automatic analyses based on amortization or sized types bound the resource usage or result size of such a procedure by a sum of unary functions of the sizes of the arguments.In this article we generalize this to arbitrary multivariate polynomial functions thus allowing bounds of the form mn which had to be grossly overestimated by m2 p n2 before. Our framework even encompasses bounds like ∑i,j≤ n mi mj where the mi are the sizes of the entries of a list of length n.This allows us for the first time to derive useful resource bounds for operations on matrices that are represented as lists of lists and to considerably improve bounds on other superlinear operations on lists such as longest common subsequence and removal of duplicates from lists of lists. Furthermore, resource bounds are now closed under composition which improves accuracy of the analysis of composed programs when some or all of the components exhibit superlinear resource or size behavior.The analysis is based on a novel multivariate amortized resource analysis. We present it in form of a type system for a simple first-order functional language with lists and trees, prove soundness, and describe automatic type inference based on linear programming.We have experimentally validated the automatic analysis on a wide range of examples from functional programming with lists and trees. The obtained bounds were compared with actual resource consumption. All bounds were asymptotically tight, and the constants were close or even identical to the optimal ones.

Multivariate amortized resource analysis

Abstract: We study the problem of automatically analyzing the worst-case resource usage of procedures with several arguments. Existing automatic analyses based on amortization, or sized types bound the resource usage or result size of such a procedure by a sum of unary functions of the sizes of the arguments.In this paper we generalize this to arbitrary multivariate polynomial functions thus allowing bounds of the form mn which had to be grossly overestimated by m2+n2 before. Our framework even encompasses bounds like ∗i,j≤n m_i mj where the mi are the sizes of the entries of a list of length n.This allows us for the first time to derive useful resource bounds for operations on matrices that are represented as lists of lists and to considerably improve bounds on other super-linear operations on lists such as longest common subsequence and removal of duplicates from lists of lists.Furthermore, resource bounds are now closed under composition which improves accuracy of the analysis of composed programs when some or all of the components exhibit super-linear resource or size behavior.The analysis is based on a novel multivariate amortized resource analysis. We present it in form of a type system for a simple first-order functional language with lists and trees, prove soundness, and describe automatic type inference based on linear programming.We have experimentally validated the automatic analysis on a wide range of examples from functional programming with lists and trees. The obtained bounds were compared with actual resource consumption. All bounds were asymptotically tight, and the constants were close or even identical to the optimal ones.

Resource aware ML

Abstract: The automatic determination of the quantitative resource consumption of programs is a classic research topic which has many applications in software development. Recently, we developed a novel multivariate amortized resource analysis that automatically computes polynomial resource bounds for first-order functional programs. In this tool paper, we describe Resource Aware ML (RAML), a functional programming language that implements our analysis. Other than in earlier articles, we focus on the practical aspects of the implementation. We describe the syntax of RAML, the code transformation prior to the analysis, the web interface, the output of the analysis, and the results of our experiments with the analysis of example programs.

A Finite Semantics of Simply-Typed Lambda Terms for Infinite Runs of Automata

Abstract: Model checking properties are often described by means of finite automata. Any particular such automaton divides the set of infinite trees into finitely many classes, according to which state has an infinite run. Building the full type hierarchy upon this interpretation of the base type gives a finite semantics for simply-typed lambda-trees. A calculus based on this semantics is proven sound and complete. In particular, for regular infinite lambda-trees it is decidable whether a given automaton has a run or not. As regular lambda-trees are precisely recursion schemes, this decidability result holds for arbitrary recursion schemes of arbitrary level, without any syntactical restriction.

Operational aspects of untyped Normalisation by Evaluation

Abstract: A purely syntactic and untyped variant of Normalisation by Evaluation for the $\lambda$-calculus is presented in the framework of a two-level $\lambda$-calculus with rewrite rules to model the inverse of the evaluation functional. Among its operational properties there is a standardisation theorem that formally establishes the adequacy of implementation in functional programming languages. An example implementation in Haskell is provided. The relation to the usual type-directed Normalisation by Evaluation is highlighted, using a short analysis of $\eta$-expansion that leads to a perspicuous strong normalisation and confluence proof for $\beta\eta\!\up$-reduction as a byproduct.

Phd by thesis

Abstract: Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

On Model-Checking Trees Generated by Higher-Order Recursion Schemes

Abstract: We prove that the modal mu-calculus model-checking problem for (ranked and ordered) node-labelled trees that are generated by order- recursion schemes (whether safe or not, and whether homogeneously typed or not) is - EXPTIME complete, for every n \geqslant 0. It follows that the monadic second-order theories of these trees are decidable. There are three major ingredients. The first is a certain transference principle from the tree generated by the scheme - the value tree - to an auxiliary computation tree, which is itself a tree generated by a related order-0 recursion scheme (equivalently, a regular tree). Using innocent game semantics in the sense of Hyland and Ong, we establish a strong correspondence between paths in the value tree and traversals in the computation tree. This allows us to prove that a given alternating parity tree automaton (APT) has an (accepting) run-tree over the value tree iff it has an (accepting) traversal-tree over the computation tree. The second ingredient is the simulation of an (accepting) traversal-tree by a certain set of annotated paths over the computation tree; we introduce traversal-simulating APT as a recognising device for the latter. Finally, for the complexity result, we prove that traversal-simulating APT enjoy a succinctness property: for deciding acceptance, it is enough to consider run-trees that have a reduced branching factor. The desired bound is then obtained by analysing the complexity of solving an associated (finite) acceptance parity game.

Multivariate amortized resource analysis

Abstract: We study the problem of automatically analyzing the worst-case resource usage of procedures with several arguments. Existing automatic analyses based on amortization or sized types bound the resource usage or result size of such a procedure by a sum of unary functions of the sizes of the arguments.In this article we generalize this to arbitrary multivariate polynomial functions thus allowing bounds of the form mn which had to be grossly overestimated by m2 p n2 before. Our framework even encompasses bounds like ∑i,j≤ n mi mj where the mi are the sizes of the entries of a list of length n.This allows us for the first time to derive useful resource bounds for operations on matrices that are represented as lists of lists and to considerably improve bounds on other superlinear operations on lists such as longest common subsequence and removal of duplicates from lists of lists. Furthermore, resource bounds are now closed under composition which improves accuracy of the analysis of composed programs when some or all of the components exhibit superlinear resource or size behavior.The analysis is based on a novel multivariate amortized resource analysis. We present it in form of a type system for a simple first-order functional language with lists and trees, prove soundness, and describe automatic type inference based on linear programming.We have experimentally validated the automatic analysis on a wide range of examples from functional programming with lists and trees. The obtained bounds were compared with actual resource consumption. All bounds were asymptotically tight, and the constants were close or even identical to the optimal ones.

Linear types and non-size-increasing polynomial time computation

Abstract: We propose a linear type system with recursion operators for inductive datatypes which ensures that all definable functions are polynomial time computable. The system improves upon previous such systems in that recursive definitions can be arbitrarily nested, in particular no predicativity or modality restrictions are made.