We present modular implicits, an extension to the OCaml language for ad-hoc polymorphism inspired by Scala implicits and modular type classes. Modular implicits are based on type-directed implicit module parameters, and elaborate straightforwardly into OCaml's first-class functors. Basing the design on OCaml's modules leads to a system that naturally supports many features from other languages with systematic ad-hoc overloading, including inheritance, instance constraints, constructor classes and associated types.
We report on the experience of developing Merlin, a language server for the OCaml programming language in development since 2013. Merlin is a daemon that connects to your favourite text editor and provides services that require a fine-grained understanding of the programming language syntax and static semantics: instant feedback on warnings and errors, autocompletion, "type of the code under the cursor", "go to definition", etc.Language servers need to handle incomplete and partially-incorrect programs, and try to be incremental to minimize recomputation after small editing actions. Merlin was built by carefully adapting the existing tools (the OCamllex lexer and Menhir parser generators) to better support incrementality, incompleteness and error handling. These extensions are elegant and general, as demonstrated by the interesting, unplanned uses that the OCaml community found for them. They could be adapted to other frontends -in any language.Besides incrementality, we discuss the way Merlin communicates with editors, describe the design decisions that went into some demanding features and report on some of the non-apparent difficulties in building good editor support, emerging from expressive programming languages or frustrating tooling ecosystems.We expect this experience report to be of interest to authors of interactive language tooling for any programming language; many design choices may be reused, and some hard-won lessons can serve as warnings.
We present a novel algorithm for reachability in an LR(1) automaton. For each transition in the automaton, the problem is to determine under what conditions this transition can be taken, that is, which (minimal) input fragment and which lookahead symbol allow taking this transition. Our algorithm outperforms Pottier's algorithm (2016) by up to three orders of magnitude on real-world grammars. Among other applications, this vastly improves the scalability of Jeffery's error reporting technique (2003), where a mapping of (reachable) error states to messages must be created and maintained.CCS Concepts: • Theory of computation → Grammars and context-free languages.
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