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We presentdecalf, adirected,effectfulcost-awarelogicalframework for studying quantitative aspects of functional programs with effects. Likecalf, the language is based on a formalphase distinctionbetween theextensionand theintensionof a program, its purebehavioras distinct from itscostmeasured by an effectful step-counting primitive. The type theory ensures that the behavior is unaffected by the cost accounting. Unlikecalf, the present language takes account ofeffects, such as probabilistic choice and mutable state. This extension requires a reformulation ofcalf’s approach to cost accounting: rather than rely on a ”separable” notion of cost, herea cost bound is simply another program. To make this formal, we equip every type with an intrinsic preorder, relaxing the precise cost accounting intrinsic to a program to a looser but nevertheless informative estimate. For example, the cost bound of a probabilistic program is itself a probabilistic program that specifies the distribution of costs. This approach serves as a streamlined alternative to the standard method of isolating a cost recurrence and readily extends to higher-order, effectful programs. The development proceeds by first introducing thedecalftype system, which is based on an intrinsic ordering among terms that restricts in the extensional phase to extensional equality, but in the intensional phase reflects an approximation of the cost of a program of interest. This formulation is then applied to a number of illustrative examples, including pure and effectful sorting algorithms, simple probabilistic programs, and higher-order functions. Finally, we justifydecalfvia a model in the topos of augmented simplicial sets. 

Amortized analysis is a program cost analysis technique for data structures in which the cost of operations is specified in aggregate, under the assumption of continued sequential use. Typically, amortized analyses are presented inductively, in terms of finite sequences of operations. We give an alternative coinductive formulation and prove that it is equivalent to the standard inductive definition. We describe a classic amortized data structure, the batched queue, and outline a coinductive proof of its amortized efficiency in calf, a dependent type theory for cost analysis. 

We presentcalf, acost-awarelogicalframework for studying quantitative aspects of functional programs. Taking inspiration from recent work that reconstructs traditional aspects of programming languages in terms of a modal account ofphase distinctions, we argue that the cost structure of programs motivates a phase distinction betweenintensionandextension. Armed with this technology, we contribute a synthetic account of cost structure as a computational effect in which cost-aware programs enjoy an internal noninterference property: input/output behavior cannot depend on cost. As a full-spectrum dependent type theory,calfpresents a unified language for programming and specification of both cost and behavior that can be integrated smoothly with existing mathematical libraries available in type theoretic proof assistants. We evaluatecalfas a general framework for cost analysis by implementing two fundamental techniques for algorithm analysis: themethod of recurrence relationsandphysicist’s method for amortized analysis. We deploy these techniques on a variety of case studies: we prove a tight, closed bound for Euclid’s algorithm, verify the amortized complexity of batched queues, and derive tight, closed bounds for the sequential andparallelcomplexity of merge sort, all fully mechanized in the Agda proof assistant. Lastly we substantiate the soundness of quantitative reasoning incalfby means of a model construction.