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Award ID contains: 2139612

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  1. ; ; ; ; (, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)
    Edwards, Jonathan; Perera, Roly; Petricek, Tomas (Ed.)
    This paper presents a comparative analysis of three implementations of the R bytecode compiler: the official R implementation, a Java-based compiler, and a Rust-based compiler. The R compiler, written in R itself, poses challenges in terms of performance and maintainability. We evaluate designs of the compilers, their trade-offs, and performance characteristics. The Rust version outperforms the Java version, which itself outperforms the R version. 
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    Free, publicly-accessible full text available January 1, 2026
  2. ; ; ; ; (, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)
    Edwards, Jonathan; Perera, Roly; Petricek, Tomas (Ed.)
    Compilers for dynamic languages often rely on intermediate representations with explicit type annotations to facilitate writing program transformations. This paper documents the design of a new typed intermediate representation for a just-in-time compiler for the R programming language called FIŘ. Type annotations, in FIŘ, capture properties such as sharing, the potential for effects, and compiler speculations. In this extended abstract, we focus on the sharing properties that may be used to optimize away some copies of values. 
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    Free, publicly-accessible full text available January 1, 2026
  3. ; ; ; (, Proceedings of the ACM on Programming Languages)
    Julia is a modern scientific-computing language that relies on multiple dispatch to implement generic libraries. While the language does not have a static type system, method declarations are decorated with expressive type annotations to determine when they are applicable. To find applicable methods, the implementation uses subtyping at run-time. We show that Julia’s subtyping is undecidable, and we propose a restriction on types to recover decidability by stratifying types into method signatures over value types—where the former can freely use bounded existential types but the latter are restricted to use-site variance. A corpus analysis suggests that nearly all Julia programs written in practice already conform to this restriction. 
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  4. ; ; ; ; (, Proceedings of the ACM on Programming Languages)
    Most code is executed more than once. If not entire programs then libraries remain unchanged from one run to the next. Just-in-time compilers expend considerable effort gathering insights about code they compiled many times, and often end up generating the same binary over and over again. We explore how to reuse compiled code across runs of different programs to reduce warm-up costs of dynamic languages. We propose to usespeculative contextual dispatchto select versions of functions from anoff-line curated code repository. That repository is a persistent database of previously compiled functions indexed by the context under which they were compiled. The repository is curated to remove redundant code and to optimize dispatch. We assess practicality by extending Ř, a compiler for the R language, and evaluating its performance. Our results suggest that the approach improves warmup times while preserving peak performance. 
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  5. ; ; ; (, ACM SIGPLAN International Conference on Programming Language Design and Implementation)
    Just-in-time compilation provides significant performance improvements for programs written in dynamic languages. These benefits come from the ability of the compiler to spec- ulate about likely cases and generate optimized code for these. Unavoidably, speculations sometimes fail and the opti- mizations must be reverted. In some pathological cases, this can leave the program stuck with suboptimal code. In this paper we propose deoptless, a technique that replaces deopti- mization points with dispatched specialized continuations. The goal of deoptless is to take a step towards providing users with a more transparent performance model in which mysterious slowdowns are less frequent and grave. 
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