We present a survey of control-flow analysis of functional programs, which has been the
subject of extensive investigation throughout the past 30 years. Analyses of the control flow …

Software engineering demands generality and abstraction, performance demands
specialization and concretization. Generative programming can provide both, but the effort …

Recent work on proof-based verifiable computation has resulted in built systems that employ
tools from complexity theory and cryptography to address a basic problem in systems …

Automatic differentiation (AD) in reverse mode (RAD) is a central component of deep
learning and other uses of large-scale optimization. Commonly used RAD algorithms such …

This paper outlines key design principles of Scilla---an intermediate-level language for
verified smart contracts. Scilla provides a clean separation between the communication …

Effect handlers have been gathering momentum as a mechanism for modular programming
with user-defined effects. Effect handlers allow for non-local control flow mechanisms such …

Deep learning has seen tremendous success over the past decade in computer vision,
machine translation, and gameplay. This success rests crucially on gradient-descent …

We bridge the gap between functional evaluators and abstract machines for the λ-calculus,
using closure conversion, transformation into continuation-passing style, and …

Forwarding is a technique for providing default attribute definitions in attribute grammars that
is helpful in the modular implementation of programming languages. It complements existing …

We show how the complexity of higher-order functional programs can be analysed
automatically by applying program transformations to a defunctionalised versions of them …