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 study the complexity of β-reduction for redexes of order 2,3 and 4. The obtained results are: evaluation of boolean expressions can be reduced to β-reduction of order 2 and β-reduction of order 2 is in O(nlog n), β-reduction of order 3 is complete for PTIME, and β-reduction of order 4 is complete for PSPACE. 1

The contribution of this paper is three-fold: 1) We analyze expressiveness of the simply typed lambda calculus (STLC) over a single base type, and show how k-DEXPTIME computations can be simulated in the order k + 6 STLC. This gives a double order improvement over the lower bound of (Hillebrand & Kanellakis 1996), reducing k-DEXPTIME to the order 2k + 3 STLC. ...

Interpretation is an implicit part of today’s programming; it has great power but is overused and has significant costs. For example, interpreters are typically significantly hard to understand and hard to reason about. The methodology of “Totally Functional Programming” (TFP) is a reasoned attempt to redress the problem of interpretation. It incorporates an awareness of the undesirability of interpretation with observations that definitions and a certain style of programming appear to offer alternatives to it. Application of TFP is expected to lead to a number of significant outcomes, theoretical as well as practical. Primary among these are novel programming languages to lessen or eliminate the use of interpretation in programming, leading to better-quality software. However, TFP contains a number of lacunae in its current formulation, which hinder development of these outcomes. Among others, formal semantics and type-systems for TFP languages are yet to be discovered, the means to reduce interpretation in programs is to be determined, and a detailed explication is needed of interpretation, definition, and the differences between the two. Most important of all however is the need to develop a complete understanding of the nature of interpretation. In this work, suitable type-systems for TFP languages are identified, and guidance given regarding the construction of appropriate formal semantics. Techniques, based around the ‘fold’ operator, are identified and developed for modifying programs so as to reduce the amount of interpretation they contain. Interpretation as a means of language-extension is also investigated. v Finally, the nature of interpretation is considered. Numerous hypotheses relating to it considered in detail. Combining the results of those analyses with discoveries from elsewhere in this work leads to the proposal that interpretation is not, in fact, symbol-based computation, but is in fact something more fundamental: computation that varies with input. We discuss in detail various implications of this characterisation, including its practical application. An often more-useful property, ‘inherent interpretiveness’, is also motivated and discussed in depth. Overall, our inquiries act to give conceptual and theoretical foundations for practical TFP.

While relational algebra and calculus are a well-established foundation for classical database query languages, it is less clear what the analog is for higher-order functions, such as query transformations. Here we study a natural way to add higher-order functionality to query languages, by adding database query operators to the λ-calculus as constants. This framework, which we refer to as λ-embedded query languages, was introduced in [BPV10]. That work had a restricted focus: the containment and equivalence problems for query-to-query functions, in the case where only positive relational operators are allowed as constants. In this work we take an in-depth look at the most basic issue for such languages: the evaluation problem. We give a full picture of the complexity of evaluation for λ-embedded query languages, looking at a number of variations: with negation and without; with only relational algebra operators, and also with a recursion mechanism in the form of a query iteration operator; in a strongly-typed calculus as well as a weakly-typed one. We give tight bounds on both the combined complexity and the query complexity of evaluation in all these settings, in the process explaining connections with Datalog and prior work on λ-calculus evaluation.