Tracking the Flow of Ideas through the Programming Languages Literature

How have conferences like ICFP, OOPSLA, PLDI, and POPL evolved over the last 20 years? Did generalizing the Call for Papers for OOPSLA in 2007 or changing the name of the umbrella conference to SPLASH in 2010 have any effect on the kinds of papers published there? How do POPL and PLDI papers compare, topic-wise? Is there related work that I am missing? Have the ideas in O\u27Hearn\u27s classic paper on separation logic shifted the kinds of papers that appear in POPL? Does a proposed program committee cover the range of submissions expected for the conference? If we had better tools for analyzing the programming language literature, we might be able to answer these questions and others like them in a data-driven way. In this paper, we explore how topic modeling, a branch of machine learning, might help the programming language community better understand our literature

Towards Practical Gradual Typing

Over the past 20 years, programmers have embraced dynamically-typed programming languages. By now, they have also come to realize that programs in these languages lack reliable type information for software engineering purposes. Gradual typing addresses this problem; it empowers programmers to annotate an existing system with sound type information on a piecemeal basis. This paper presents an implementation of a gradual type system for a full-featured class-based language as well as a novel performance evaluation framework for gradual typing

Type-Directed Operational Semantics for Gradual Typing

The semantics of gradually typed languages is typically given indirectly via an elaboration into a cast calculus. This contrasts with more conventional formulations of programming language semantics, where the semantics of a language is given directly using, for instance, an operational semantics. This paper presents a new approach to give the semantics of gradually typed languages directly. We use a recently proposed variant of small-step operational semantics called type-directed operational semantics (TDOS). In TDOS type annotations become operationally relevant and can affect the result of a program. In the context of a gradually typed language, such type annotations are used to trigger type-based conversions on values. We illustrate how to employ TDOS on gradually typed languages using two calculi. The first calculus, called ? B^g, is inspired by the semantics of the blame calculus, but it has implicit type conversions, enabling it to be used as a gradually typed language. The second calculus, called ? B^r, explores a different design space in the semantics of gradually typed languages. It uses a so-called blame recovery semantics, which enables eliminating some false positives where blame is raised but normal computation could succeed. For both calculi, type safety is proved. Furthermore we show that the semantics of ? B^g is sound with respect to the semantics of the blame calculus, and that ? B^r comes with a gradual guarantee. All the results have been mechanically formalized in the Coq theorem prover

Space-Efficient Gradual Typing in Coercion-Passing Style

Herman et al. pointed out that the insertion of run-time checks into a gradually typed program could hamper tail-call optimization and, as a result, worsen the space complexity of the program. To address the problem, they proposed a space-efficient coercion calculus, which was subsequently improved by Siek et al. The semantics of these calculi involves eager composition of run-time checks expressed by coercions to prevent the size of a term from growing. However, it relies also on a nonstandard reduction rule, which does not seem easy to implement. In fact, no compiler implementation of gradually typed languages fully supports the space-efficient semantics faithfully. In this paper, we study coercion-passing style, which Herman et al. have already mentioned, as a technique for straightforward space-efficient implementation of gradually typed languages. A program in coercion-passing style passes "the rest of the run-time checks" around - just like continuation-passing style (CPS), in which "the rest of the computation" is passed around - and (unlike CPS) composes coercions eagerly. We give a formal coercion-passing translation from ?S by Siek et al. to ?S?, which is a new calculus of first-class coercions tailored for coercion-passing style, and prove correctness of the translation. We also implement our coercion-passing style transformation for the Grift compiler developed by Kuhlenschmidt et al. An experimental result shows stack overflow can be prevented properly at the cost of up to 3 times slower execution for most partially typed practical programs

Manifest Contracts

Eiffel popularized design by contract, a software design philosophy where programmers specify the requirements and guarantees of functions via executable pre- and post-conditions written in code. Findler and Felleisen brought contracts to higher-order programming, inspiring the PLT Racket implementation of contracts. Existing approaches for runtime checking lack reasoning principles and stop short of their full potential---most Racket contracts check only simple types. Moreover, the standard algorithm for higher-order contract checking can lead to unbounded space consumption and can destroy tail recursion. In this dissertation, I develop so-called manifest contract systems which integrate more coherently in the type system, and relate them to Findler-and-Felleisen-style latent contracts. I extend a manifest system with type abstraction and relational parametricity, and also show how to integrate dynamic types and contracts in a space efficient way, i.e., in a way that doesn\u27t destroy tail recursion. I put manifest contracts on a firm type-theoretic footing, showing that they support extensions necessary for real programming. Developing these principles is the first step in designing and implementing higher-order languages with contracts and refinement types

TOWARDS EFFICIENT GRADUAL TYPING VIA MONOTONIC REFERENCES AND COERCIONS

Thesis (Ph.D.) - Indiana University, Luddy School of Informatics, Computing, and Engineering/University Graduate School, 2020Integrating static and dynamic typing into a single programming language enables programmers to choose which discipline to use in each code region. Different approaches for this integration have been studied and put into use at large scale, e.g. TypeScript for JavaScript and adding the dynamic type to C#. Gradual typing is one approach to this integration that preserves type soundness by performing type-checking at run-time using casts. For higher order values such as functions and mutable references, a cast typically wraps the value in a proxy that performs type-checking when the value is used. This approach suffers from two problems: (1) chains of proxies can grow and consume unbounded space, and (2) statically typed code regions need to check whether values are proxied. Monotonic references solve both problems for mutable references by directly casting the heap cell instead of wrapping the reference in a proxy. In this dissertation, an integration is proposed of monotonic references with the coercion-based solution to the problem of chains of proxies for other values such as functions. Furthermore, the prior semantics for monotonic references involved storing and evaluating cast expressions (not yet values) in the heap and it is not obvious how to implement this behavior efficiently in a compiler and run-time system. This dissertation proposes novel dynamic semantics where only values are written to the heap, making the semantics straightforward to implement. The approach is implemented in Grift, a compiler for a gradually typed programming language, and a few key optimizations are proposed. Finally, the proposed performance evaluation methodology shows that the proposed approach eliminates all overheads associated with gradually typed references in statically typed code regions without introducing significant average-case overhead