The abuse of structural rules may have damaging complexity effects.

We investigate the expressive power of the typed -calculus when expressing computations over finite structures, i.e., databases. We show that the simply typed -calculus can express various database query languages such as the relational algebra, fixpoint logic, and the complex object algebra. In our embeddings, inputs and outputs are -terms encoding databases, and a program expressing a query is a -term which types when applied to an input and reduces to an output.

Compare first-order functional programs with higher-order programs allowing functions as function parameters. Can the the first program class solve fewer problems than the second? The answer is no: both classes are Turing complete, meaning that they can compute all partial recursive functions. In particular, higher-order values may be first-order simulated by use of the list constructor ‘cons’ to build function closures. This paper uses complexity theory to prove some expressivity results about small programming languages that are less than Turing complete. Complexity classes of decision problems are used to characterize the expressive power of functional programming language features. An example: second-order programs are more powerful than first-order, since a function f of type [Bool]-〉Bool is computable by a cons-free first-order functional program if and only if f is in PTIME, whereas f is computable by a cons-free second-order program if and only if f is in EXPTIME. Exact characterizations are given for those problems of type [Bool]-〉Bool solvable by programs with several combinations of operations on data: presence or absence of constructors; the order of data values: 0, 1, or higher; and program control structures: general recursion, tail recursion, primitive recursion.

We present a functional framework for database query languages, which is analogous to the conventional logical framework of first-order and fixpoint formulas over finite structures. We use atomic constants of order 0, equality among these constants, variables, application, lambda abstraction, and let abstraction; all typed using fixed order ( 5) functionalities. In this framework, proposed in [21] for arbitrary order functionalities, queries and databases are both typed lambda terms, evaluation is by reduction, and the main programming technique is list iteration. We define two families of languages: TLI = i or simply-typed list iteration of order i +3 with equality, and MLI = i or ML-typed list iteration of order i+3 with equality; we use i+3 since our list representation of databases requires at least order 3. We show that: FO-queries ` TLI = 0 ` MLI = 0 ` LOGSPACE-queries ` TLI = 1 = MLI = 1 = PTIME-queries ` TLI = 2 , where equality is no longer a primitive in TLI = 2 . We also show that ML type inference, restricted to fixed order, is polynomial in the size of the program typed. Since programming by using low order functionalities and type inference is common in functional languages, our results indicate that such programs suffice for expressing efficient computations and that their ML-types can be efficiently inferred.

Abstract not found

Church's simply typed -calculus is a very basic framework for functional programming language research. However, it is common to augment this framework with additional programming constructs, because its expressive power for functions over the domain of Church numerals is very limited. In this thesis: (1) We re-examine the expressive power of the "pure" simply typed -calculus, but over encodings of finite relational structures, i. e., finite models or databases . In this novel framework the simply typed -calculus expresses all elementary functions from finite models to finite models. In addition, many common database query languages, e. g., relational algebra, Datalog : , and the Abiteboul/Beeri complex object algebra, can be embedded into it. The embeddings are feasible in the sense that the -terms corresponding to PTIME queries can be evaluated in polynomial time. (2) We examine fixed-order fragments of the simply typed -calculus to determine machine independent characterizations of complexity classes. For this we augment the calculus with atomic constants and equality among atomic constants. We show that over ordered structures, the order 3, 4, 5, and 6 fragments express exactly the first-order, PTIME, PSPACE, and EXPTIME queries, respectively, and we conjecture that for general k 1, order 2 k + 4 expresses exactly the k-EXPTIME queries and order 2 k + 5 expresses exactly the k-EXPSPACE queries. (3) We also re-examine other functional characterizations of PTIME and we show that method schemas with ordered objects express exactly PTIME. This is a first-order framework proposed for object-oriented databases---as opposed to the above higher-order frameworks. In summary, this research provides a link between finite model theory (and thus computational complexity), dat...

Core-ML is a basic subset of most functional programming languages. It consists of the simply typed (or monomorphic) -calculus, simply typed equality over atomic constants, and let as the only polymorphic construct. We present a synthesis of recent results which characterize this "toy" language's expressive power as well as its type reconstruction (or type inference) problem. More specifically: (1) Core-ML can express exactly the ELEMENTARY queries, where a program input is a database encoded as a -term and a query program is a -term whose application to the input normalizes to the output database. In addition, it is possible to express all the PTIME queries so that this normalization process is polynomial in the input size. (2) The polymorphism of let can be explained using a simple algorithmic reduction to monomorphism, and provides flexibility, without affecting expressibility. Algorithms for type reconstruction offer the additional convenience of static typing without type declarations. Given polymorphism, the price of this convenience is an increase in complexity from linear-time in the size of the program typed (without let) to completeness in exponential-time (with let).

Abstract – We study the computational model of polygraphs. For that, we consider polygraphic programs, a subclass of these objects, as a formal description of first-order functional programs. We explain their semantics and prove that they form a Turing-complete computational model. Their algebraic structure is used by analysis tools, called polygraphic interpretations, for complexity analysis. In particular, we delineate a subclass of polygraphic programs that compute exactly the functions that are Turingcomputable in polynomial time.

We present a functional framework for descriptive computational complexity, in which the Regular, Firstorder, Ptime, Pspace, k-Exptime, k-Expspace (k 1), and Elementary sets have syntactic characterizations. In this framework, typed lambda terms represent inputs and outputs as well as programs. The lambda calculi describing the above computational complexity classes are simply or let-polymorphically typed with functionalities of fixed order. They consist of: order 0 atomic constants, order 1 equality among these constants, variables, application, and abstraction. Increasing functionality order by one for these languages corresponds to increasing the computational complexity by one alternation. This exact correspondence is established using a semantic evaluation of languages for each fixed order, which is the primary technical contribution of this paper.

Abstract. We a give an intrinsic characterization of the class of functions which are computable in NC 1 that is by a uniform, logarithmic depth and polynomial size family circuit. Recall that the class of functions in ALogTime, that is in logarithmic time on an Alternating Turing Machine, is NC 1. Our characterization is in terms of first order functional programming languages. We define measure-tools called Supinterpretations, which allow to give space and time bounds and allow also to capture a lot of program schemas. This study is part of a research on static analysis in order to predict program resources. It is related to the notion of Quasi-interpretations and belongs to the implicit computational complexity line of research. 1