This article extends tail-call optimisation by applying it to asynchronous calls. We first introduce TMA, a novel code transformation for asynchronous tail recursive functions that prevents the creation of unnecessary tasks. We then show how to combine TMA with the existing TMC optimisation; we obtain an optimisation able to turn a recursive function with multiple tail calls under constructors into a parallel version of the function, also optimised in space. We formalise both optimisations over representative calculi, and prove them correct through backward simulations. Finally, we provide a proof-of-concept implementation as an OCaml syntax extension and evaluate it experimentally, showing our approach optimises both memory and execution time

We present ZipML , a new path-based type system for a fully fledged ML-module language that avoids the signature avoidance problem. This is achieved by introducing floating fields , which act as additional fields of a signature, invisible to the user but still accessible to the typechecker. In practice, they are handled as zippers on signatures, and can be seen as a lightweight extension of existing signatures. Floating fields allow to delay the resolution of instances of the signature avoidance problem as long as possible or desired. Since they do not exist at runtime, they can be simplified along type equivalence, and dropped once they became unreachable. We give rewriting rules for the simplification of floating fields without loss of type-sharing and present an algorithm that implements them. Remaining floating fields may fully disappear at signature ascription, especially in the presence of toplevel interfaces. Residual unavoidable floating fields can be shown to the user as a last resort, improving the quality of error messages. Besides, ZipML implements early and lazy strengthening, as well as lazy inlining of definitions, preventing duplication of signatures inside the typechecker. The correctness of the type system is proved by elaboration into M ω , which has itself been proved sound by translation to F ω . ZipML has been designed to be an improvement over OCaml that could be retrofitted into the existing implementation.

Hardware verification is crucial to ensure the quality of Integrated Circuits, and prevent costly bugs down the manufacturing flow. Electrical Rule Checking (ERC) is a verification step used to assert that a circuit complies with some electrical rules, from the absence of short-circuits to dedicated constructor rules. In this survey, we provide a global overview of existing ERC techniques at transistor-level, where voltage values are explicit. We propose a new classification method to compare the existing approaches based on their semantic modeling of circuits. This survey precisely describes transistor-level ERC research challenges and existing solutions. We believe it will help structure this research domain by positioning existing approaches with respect to each other. Obviously, a survey should also facilitate technological transfer and this one should help CAD vendors identify the most relevant approaches to integrate in their tools. Finally, we highlight several promising directions to improve the existing solutions.

We present a novel technique for Electrical Rule Checking (ERC) based on formal methods. We define a relational semantics of Integrated Circuits (IC) as a means to model circuits' behavior at transistor-level. We use Z3, a Satisfiability Modulo Theory (SMT) solver, to verify electrical properties on circuits – thanks to the defined semantics. We demonstrate the usability of the approach to detect current leakage due to missing level-shifter on large industrial circuits, and we conduct experiments to study the scalability of the approach.

ML modules come as an additional layer on top of a core language to offer large-scale notions of composition and abstraction. They largely contributed to the success of OCaml and SML. While modules are easy to write for common cases, their advanced use may become tricky. Additionally, despite a long line of works, their meta-theory remains difficult to comprehend, with involved soundness proofs. In fact, the module layer of OCaml does not currently have a formal specification and its implementation has some surprising behaviors. Building on previous translations from ML modules to Fω, we propose a type system, called Mω, that covers a large subset of OCaml modules, including both applicative and generative functors, and extended with transparent ascription. This system produces signatures in an OCaml-like syntax extended with Fω quantifiers. We provide a reverse translation from Mω signatures to path-based source signatures along with a characterization of signature avoidance cases, making Mω signatures well suited to serve as a new internal representation for a typechecker. The soundness of the type system is shown by elaboration in Fω. We improve over previous encodings of sealing within applicative functors, by the introduction of transparent existential types, a weaker form of existential types that can be lifted out of universal and arrow types. This shines a new light on the form of abstraction provided by applicative functors and brings their treatment much closer to those of generative functors.

We consider the verification of electrical properties of circuits to identify potential violations of electrical design rules, also called Electrical Rule Checking (ERC). We present a general approach based on Satisfiability Modulo Theory (SMT) to verify that these errors cannot occur in a given circuit. We claim that our approach is scalable and more precise than existing analyses, like voltage propagation. We applied these techniques to a specific type of errors, the missing level shifters. On an industrial case-study, our technique is able to flag 31 % of the warnings raised by the voltage propagation analysis as being false alarms.

Initially present only in functional languages such as OCaml and Haskell, Algebraic Data Types (ADTs) have now become pervasive in mainstream languages, providing nice data abstractions and an elegant way to express functions through pattern matching. Unfortunately, ADTs remain seldom used in low-level programming. One reason is that their increased convenience comes at the cost of abstracting away the exact memory layout of values. Even Rust, which tries to optimize data layout, severely limits control over memory representation. In this article, we present a new approach to specify the data layout of rich data types based on a dual view: a source type, providing a high-level description available in the rest of the code, along with a memory type, providing full control over the memory layout. This dual view allows for better reasoning about memory layout, both for correctness, with dedicated validity criteria linking the two views, and for optimizations that manipulate the memory view. We then provide algorithms to compile constructors and destructors, including pattern matching, to their low-level memory representation. We prove our compilation algorithms correct, implement them in a tool called ribbit that compiles to LLVM IR, and show some early experimental results.

Algebraic data types and pattern matching are popular tools to build programs manipulating complex datastructures in a safe yet efficient manner. On top of its safety advantages, compilation techniques can turn pattern matching into highly efficient deconstruction code for immutable use cases. Conversely, high-performance datastructures and languages prefer to leverage (controlled) mutations to maximize time and memory efficiency. Algebraic data types provide a natural framework to efficiently describe in-place transformations as rewrite rules. Such representation could take advantage of parallelism opportunities that appear in tree-like structures.

Systems programming often requires the manipulation of resources like file handles, network connections, or dynamically allocated memory. Programmers need to follow certain protocols to handle these resources correctly. Violating these protocols causes bugs ranging from type mismatches over data races to use-after-free errors and memory leaks. These bugs often lead to security vulnerabilities. While statically typed programming languages guarantee type soundness and memory safety by design, most of them do not address issues arising from improper handling of resources. An important step towards handling resources is the adoption of linear and affine types that enforce single-threaded resource usage. However, the few languages supporting such types require heavy type annotations. We present Affe, an extension of ML that manages linearity and affinity properties using kinds and constrained types. In addition Affe supports the exclusive and shared borrowing of affine resources, inspired by features of Rust. Moreover, Affe retains the defining features of the ML family: it is an impure, strict, functional expression language with complete principal type inference and type abstraction. does not require any linearity annotations in expressions and supports common functional programming idioms.

Regular expressions are part of every programmer’s toolbox. They are used for a wide variety of language-related tasks and there are many algorithms for manipulating them. In particular, matching algorithms that detect whether a word belongs to the language described by a regular expression are well explored, yet new algorithms appear frequently. However, there is no satisfactory methodology for testing such matchers. We propose a testing methodology which is based on generating positive as well as negative examples of words in the language. To this end, we present a new algorithm to generate the language described by a generalized regular expression with intersection and complement operators. The complement operator allows us to generate both positive and negative example words from a given regular expression. We implement our generator in Haskell and OCaml and show that its performance is more than adequate for testing.

We present a complete method for synthesizing lexicographic linear ranking functions (and thus proving termination), supported by inductive invariants, in the case where the transition relation of the program includes disjunctions and existentials (large block encoding of control flow). Previous work would either synthesize a ranking function at every basic block head, not just loop headers, which reduces the scope of programs that may be proved to be terminating, or expand large block transitions including tests into (exponentially many) elementary transitions, prior to computing the ranking function, resulting in a very large global constraint system. In contrast, our algorithm incrementally refines a global linear constraint system according to extremal counterexamples: only constraints that exclude spurious solutions are included. Experiments with our tool Termite show marked performance and scalability improvements compared to other systems.

Language-integrated query techniques have been explored in a number of different language designs. We consider two different, type-safe approaches employed by Links and F#. Both approaches provide rich dynamic query generation capabilities, and thus amount to a form of heterogeneous staged computation, but to date there has been no formal investigation of their relative expressiveness. We present two core calculi Eff and Quot, respectively capturing the essential aspects of language-integrated querying using effects in Links and quotation in LINQ. We show via translations from Eff to Quot and back that the two approaches are equivalent in expressiveness. Based on the translation from Eff to Quot, we extend a simple Links compiler to handle queries.