A framework and methodology—termed LogiKEy—for the design and engineering of ethical
reasoners, normative theories and deontic logics is presented. The overall motivation is the …

Symbolic execution is a powerful program analysis and testing technique. Symbolic
execution engines are usually implemented as interpreters, and the induced interpretation …

Machine learning (ML) pipelines for model training and validation typically include
preprocessing, such as data cleaning and feature engineering, prior to training an ML …

Modularity is a key concern in programming. However, programming languages remain
limited in terms of modularity and extensibility. Small canonical problems, such as the …

It is well-known that the simply typed lambda-calculus is modeled by any cartesian closed
category (CCC). This correspondence suggests giving typed functional programs a variety of …

Automatic differentiation (AD) has been a topic of interest for researchers in many
disciplines, with increased popularity since its application to machine learning and neural …

In 1989 when functional programming was still considered a niche topic, Hughes wrote a
visionary paper arguing convincingly 'why functional programming matters'. More than two …

Parser combinators are a middle ground between the fine control of hand-rolled parsers and
the high-level almost grammar-like appearance of parsers created via parser generators …

Macros provide a powerful means of extending languages. They have proven useful in both
general-purpose and domain-specific programming contexts. This paper presents an …

Popular programming techniques such as shallow embeddings of Domain Specific
Languages (DSLs), finally tagless or object algebras are built on the principle of …