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We reflect on programming with complicated effects, recalling an undeservingly forgotten alternative to monadic programming and checking to see how well it can actually work in modern functional languages. We adopt and argue the position of factoring an effectful program into a first-order effectful DSL with a rich, higher-order macro system. Not all programs can be thus factored. Although the approach is not general-purpose, it does admit interesting programs. The effectful DSL is likewise rather problem-specific and lacks general-purpose monadic composition, or even functions. On the upside, it expresses the problem elegantly, is simple to implement and reason about, and lends itself to non-standard interpretations such as code generation (compilation) and abstract interpretation. A specialized DSL is liable to be frequently extended; the experience with the tagless-final style of DSL embedding shown that the DSL evolution can be made painless, with the maximum code reuse. We illustrate the argument on a simple but representative example of a rather complicated effect -- non-determinism, including committed choice. Unexpectedly, it turns out we can write interesting non-deterministic programs in an ML-like language just as naturally and elegantly as in the functional-logic language Curry -- and not only run them but also statically analyze, optimize and compile. The richness of the Meta Language does, in reality, compensate for the simplicity of the effectful DSL. The key idea goes back to the origins of ML as the Meta Language for the Edinburgh LCF theorem prover. Instead of using ML to build theorems, we now build (DSL) programs.
We investigate representations of imperative programs as constrained Horn clauses. Starting from operational semantics transition rules, we proceed by writing interpreters as constrained Horn clause programs directly encoding the rules. We then speci
This paper is a contribution to the search for efficient and high-level mathematical tools to specify and reason about (abstract) programming languages or calculi. Generalising the reduction monads of Ahrens et al., we introduce transition monads, th
It is well-known that big-step semantics is not able to distinguish stuck and non-terminating computations. This is a strong limitation as it makes very difficult to reason about properties involving infinite computations, such as type soundness, whi
We introduce a new application for inductive logic programming: learning the semantics of programming languages from example evaluations. In this short paper, we explored a simplified task in this domain using the Metagol meta-interpretive learning s
We present a self-certifying compiler for the COGENT systems language. COGENT is a restricted, polymorphic, higher-order, and purely functional language with linear types and without the need for a trusted runtime or garbage collector. It compiles to