Freer monads are a useful structure commonly used in various domains due to their expressiveness. However, a known issue with freer monads is that they are not amenable to static analysis. This paper explores freer arrows, a relatively expressive structure that is amenable to static analysis. We propose several variants of freer arrows. We conduct a case study on choreographic programming to demonstrate the usefulness of freer arrows in Haskell.

In recent years, the microservice architecture has become the standard technique for building scalable applications, yet it still confronts developers with numerous challenges. Splitting an application into separate pieces can lead to unpredictable performance, and the process of doing so is complex and labor-intensive. Although a variety of solutions exist to simplify distributed application development, their programming abstractions offer poor support for existing applications in need of scaling. In this paper, we propose Monolift, a new technique for developing distributed applications that prioritizes incremental adoption and support for legacy code. Our proposal treats distribution as a compiler pass, allowing users to guide the distribution process with lightweight code-level annotations, and supports dynamic distribution strategies based on performance metrics rather than development-time decisions. We show that our Monolift prototype can automatically synthesize a variety of distributed architectures from the same source code, each having different performance tradeoffs, and that Monolift's dynamic distribution mechanisms outperform static microservice architectures under varying run-time conditions.

Choreographic programming (CP) is a paradigm for implementing distributed systems that uses a single global program to define the actions and interactions of all participants. Library-level CP implementations, like HasChor, integrate well with mainstream programming languages but have several limitations: Their conditionals require extra communication; they require specific host-language features ( e.g ., monads); and they lack support for programming patterns that are essential for implementing realistic distributed applications. We make three contributions to library-level CP to specifically address these challenges. First, we propose and formalize conclaves and multiply-located values, which enable efficient conditionals in library-level CP without redundant communication. Second, we propose census polymorphism, a technique for abstracting over the number of participants in a choreography. Third, we introduce a design pattern for library-level CP in host languages without support for monads. We demonstrate these contributions via implementations in Haskell, Rust, and TypeScript.

Conflict-free replicated data types (CRDTs) are distributed data structures designed for fault tolerance and high availability. CRDTs have historically been taxonomized into state-based CRDTs, in which replicas apply updates locally and periodically broadcast their state to other replicas over the network, and operation-based (or op-based ) CRDTs, in which every state-updating operation is individually broadcast. In the literature, state-based and op-based CRDTs are considered equivalent due to the existence of algorithms that let them emulate each other, and verification techniques and results that apply to one kind of CRDT are said to apply to the other thanks to this equivalence. However, what it means for state-based and op-based CRDTs to emulate each other has never been made fully precise. Emulation is nontrivial since state-based and op-based CRDTs place different requirements on the underlying network with regard to both the causal ordering of message delivery, and the granularity of the messages themselves. We specify and formalize CRDT emulation in terms of simulation by modeling CRDTs and their interactions with the network as transition systems. We show that emulation can be understood as weak simulations between the transition systems of the original and emulating CRDT systems, thus closing a gap in the CRDT literature. We precisely characterize which properties of CRDT systems are preserved by our weak simulations, and therefore which properties can be said to be preserved by emulation algorithms. Finally, we leverage our emulation results to obtain a general representation independence result for CRDTs: intuitively, clients of a CRDT cannot tell whether they are interacting with a state-based or op-based CRDT in particular.

The Entity-Component-System (ECS) software design pattern, long used in game development, encourages a clean separation of identity (entities), data properties (components), and computational behaviors (systems). Programs written using the ECS pattern are naturally concurrent, and the pattern offers modularity, flexibility, and performance benefits that have led to a proliferation of ECS frameworks. Nevertheless, the ECS pattern is little-known and not well understood outside of a few domains. Existing explanations of the ECS pattern tend to be mired in the concrete details of particular ECS frameworks, or they explain the pattern in terms of imperfect metaphors or in terms of what it is not. We seek a rigorous understanding of the ECS pattern via the design of a formal model, Core ECS, that abstracts away the details of specific implementations to reveal the essence of software using the ECS pattern. We identify a class of Core ECS programs that behave deterministically regardless of scheduling, enabling use of the ECS pattern as a deterministic-by-construction concurrent programming model. With Core ECS as a point of comparison, we then survey several real-world ECS frameworks and find that they all leave opportunities for deterministic concurrency unexploited. Our findings point out a space for new ECS implementation techniques that better leverage such opportunities.

The Lamport diagram is a pervasive and intuitive tool for informal reasoning about “happens-before” relationships in a concurrent system. However, traditional axiomatic formalizations of Lamport diagrams can be painful to work with in a mechanized setting like Agda. We propose an alternative, inductive formalization — the causal separation diagram (CSD) — that takes inspiration from string diagrams and concurrent separation logic, but enjoys a graphical syntax similar to Lamport diagrams. Critically, CSDs are based on the idea that causal relationships between events are witnessed by the paths that information follows between them. To that end, we model “happens-before” as a dependent type of paths between events. The inductive formulation of CSDs enables their interpretation into a variety of semantic domains. We demonstrate the interpretability of CSDs with a case study on properties of logical clocks , widely-used mechanisms for reifying causal relationships as data. We carry out this study by implementing a series of interpreters for CSDs, culminating in a generic proof of Lamport’s clock condition that is parametric in a choice of clock. We instantiate this proof on Lamport’s scalar clock, on Mattern’s vector clock, and on the matrix clocks of Raynal et al. and of Wuu and Bernstein, yielding verified implementations of each. The CSD formalism and our case study are mechanized in the Agda proof assistant.

The Glasgow Haskell Compiler is known for its feature-laden runtime system (RTS), which includes lightweight threads, asynchronous exceptions, and a slew of other features. Their combination is powerful enough that a programmer may complete the same task in many different ways --- some more advisable than others.

Choreographic programming is an emerging paradigm for programming distributed systems. In choreographic programming, the programmer describes the behavior of the entire system as a single, unified program -- a choreography -- which is then compiled to individual programs that run on each node, via a compilation step called endpoint projection. We present a new model for functional choreographic programming where choreographies are expressed as computations in a monad. Our model supports cutting-edge choreographic programming features that enable modularity and code reuse: in particular, it supports higher-order choreographies, in which a choreography may be passed as an argument to another choreography, and location-polymorphic choreographies, in which a choreography can abstract over nodes. Our model is implemented in a Haskell library, HasChor , which lets programmers write choreographic programs while using the rich Haskell ecosystem at no cost, bringing choreographic programming within reach of everyday Haskellers. Moreover, thanks to Haskell's abstractions, the implementation of the HasChor library itself is concise and understandable, boiling down endpoint projection to its short and simple essence.

This paper presents an extension to Liquid Haskell that facilitates stating and semi-automatically proving properties of typeclasses. Liquid Haskell augments Haskell with refinement types —our work allows such types to be attached to typeclass method declarations, and ensures that instance implementations respect these types. The engineering of this extension is a modular interaction between GHC, the Glasgow Haskell Compiler, and Liquid Haskell’s core proof infrastructure. The design sheds light on the interplay between modular proofs and typeclass resolution, which in Haskell is coherent by default (meaning that resolution always selects the same implementation for a particular instantiating type), but in other dependently typed languages is not. We demonstrate the utility of our extension by using Liquid Haskell to modularly verify that 34 instances satisfy the laws of five standard typeclasses. More substantially, we implement a framework for programming distributed applications based on replicated data types (RDTs). We define a typeclass whose Liquid Haskell type captures the mathematical properties RDTs should satisfy; prove in Liquid Haskell that these properties are sufficient to ensure that replicas’ states converge despite out-of-order update delivery; implement (and prove correct) several instances of our RDT typeclass; and use them to build two realistic applications, a multi-user calendar event planner and a collaborative text editor.

Computational scientists often prototype software using productivity languages that offer high-level programming abstractions. When higher performance is needed, they are obliged to rewrite their code in a lower-level efficiency language. Different solutions have been proposed to address this trade-off between productivity and efficiency. One promising approach is to create embedded domain-specific languages that sacrifice generality for productivity and performance, but practical experience with DSLs points to some road blocks preventing widespread adoption. This paper proposes a non-invasive domain-specific language that makes as few visible changes to the host programming model as possible. We present ParallelAccelerator, a library and compiler for high-level, high-performance scientific computing in Julia. ParallelAccelerator's programming model is aligned with existing Julia programming idioms. Our compiler exposes the implicit parallelism in high-level array-style programs and compiles them to fast, parallel native code. Programs can also run in "library-only" mode, letting users benefit from the full Julia environment and libraries. Our results show encouraging performance improvements with very few changes to source code required. In particular, few to no additional type annotations are necessary.

A fundamental challenge of parallel programming is to ensure that the observable outcome of a program remains deterministic in spite of parallel execution. Language-level enforcement of determinism is possible, but existing deterministic-by-construction parallel programming models tend to lack features that would make them applicable to a broad range of problems. Moreover, they lack extensibility: it is difficult to add or change language features without breaking the determinism guarantee.

Deterministic-by-construction parallel programming models offer the advantages of parallel speedup while avoiding the nondeterministic, hard-to-reproduce bugs that plague fully concurrent code. A principled approach to deterministic-by-construction parallel programming with shared state is offered by LVars: shared memory locations whose semantics are defined in terms of an application-specific lattice. Writes to an LVar take the least upper bound of the old and new values with respect to the lattice, while reads from an LVar can observe only that its contents have crossed a specified threshold in the lattice. Although it guarantees determinism, this interface is quite limited.