arXiv subjects

Oliver Bračevac

Publications and source records attributed to Oliver Bračevac.

11 recordsLinked to original sources

arXiv2026

Classifying Capabilities (Extended Version)

Capture checking in Scala 3 enables lightweight and practical effect and resource tracking by recording capabilities in types. However, the system offers no way to reason about kinds of capabilities. Natural constraints such as "retaining only the control-flow capabilities of this closure" or "excluding all thread-local capabilities from this argument" become inexpressible. Both arise in the Scala 3 standard library: "Try" re-throws caught exceptions, so it retains only the control-flow capabilities of its body, and "Future" must not capture thread-local resources. The inability to state these constraints has kept parts of the library outside capture checking. We introduce capability classifiers: a tree-structured, user-extensible hierarchy of tags that classify capabilities by their semantic role. Projections filter capture sets by classifier, supporting both inclusion ("c.only[C]") and exclusion ("c.except[C]"). The tree structure enables decidable disjointness reasoning: classifiers on separate branches are guaranteed to be disjoint regardless of unknown extensions elsewhere in the hierarchy. We formalize classifiers as an extension of System Capless, a core calculus for capture checking, introducing a classifier kind algebra based on intersection, union, and subtraction of classifier subtrees. We extend the operational semantics to model exception interception and establish type safety, effect safety, and handler coverage via a big-step proof, fully mechanized in Lean 4. Classifiers are implemented in the Scala 3 capture checker, and we demonstrate their use on standard library types and real-world effect exclusion patterns.

cs.PL↗

arXiv2026

System Capybara: Tracking Capabilities for Separation and Freshness (Extended Version)

Substructural type systems give strong static control over aliasing. Examples include uniqueness, separation, and borrowing. How can such control be brought to established languages whose programming models rely on higher-order abstraction, unrestricted aliasing, and pervasive sharing? We study this problem in the context of Scala. We show how to retrofit these guarantees selectively instead of globally: ordinary code keeps Scala's usual aliasing discipline, while stronger guarantees can be enforced where they matter. Our starting point is Scala's capture checking, whose treatment of capabilities is inspired by the object-capability tradition: capabilities are ordinary values, and capture sets record, in a value's type, which capabilities the value may use. We develop System Capybara, which adds a selective alias-control layer to this mechanism. By tracking separation, consumption, freshness, and read-only access for capabilities, Capybara recovers key reasoning principles from substructural and ownership-based disciplines without global invariants. We give a type-preserving translation from the surface calculus Capybara to CoreCapybara, a core calculus extending System Capless, the earlier foundation for capture checking. The translation uses quantifiers for capture polymorphism and freshness, and constraint-indexed modal types for separation. We prove a semantic soundness result for the core calculus in Lean 4 and derive type safety, memory safety (no use-after-free or double-free), immutability of read-only computations, and data-race freedom for well-typed programs. Finally, we implement Scala 3's new separation checker, which brings higher-order separation reasoning about effects, capabilities, and resources to ordinary Scala, including fearless concurrency.

cs.PL↗

arXiv2026

LACUNA: Safe Agents as Recursive Program Holes

LLM agents increasingly act by writing code, yet a split persists between the runtime that drives the agent and the code the model writes. The runtime owns the loop, context, and control flow, and the model has little say over any of them. Letting model-written code shape the runtime itself would make agents more expressive, but it would also sharpen safety problems. A model can be diverted by a prompt injection, call the wrong tool, or fail partway and leave an inconsistent state, and each such failure reaches further when the code shapes the runtime than when it expresses a single action. We present LACUNA, a programming model for agents that closes this split while preserving safety. Each agent action is a typed call $\texttt{agent[T](task)}$ that the LLM fills with code when execution reaches it, and the code is type-checked against the surrounding program before it runs. Because each action is accepted or rejected as a whole, a rejected one leaves the environment untouched, and its compiler diagnostics drive a retry. The same check also bounds which tools and data an action may use and how they flow. Our primitive expresses ReAct loops, sub-agents, skills, parallel decomposition, and multi-model planning as ordinary control flow. We evaluate LACUNA on a collection of test cases, BrowseComp-Plus, and $τ^2$-bench. On BrowseComp-Plus, $8.6\%$ of generations are rejected before execution, with 0.7 retries per query on average, and the agent reaches $27.1\%$ accuracy. On $τ^2$-bench, LACUNA solves $76.0\%$ of $392$ tasks across four domains with a capable model, on par with the baseline agent.

cs.AI↗

arXiv2026

Tracking Capabilities for Safer Agents

AI agents that interact with the real world through tool calls pose fundamental safety challenges: agents might leak private information, cause unintended side effects, or be manipulated through prompt injection. To address these challenges, we propose to put the agent in a programming-language-based "safety harness": instead of calling tools directly, agents express their intentions as code in a capability-safe language: Scala 3 with capture checking. Capabilities are program variables that regulate access to effects and resources of interest. Scala's type system tracks capabilities statically, providing fine-grained control over what an agent can do. In particular, it enables local purity, the ability to enforce that sub-computations are side-effect-free, preventing information leakage when agents process classified data. We demonstrate that extensible agent safety harnesses can be built by leveraging a strong type system with tracked capabilities. Our experiments show that agents can generate capability-safe code with no significant loss in task performance, while the type system reliably prevents unsafe behaviors such as information leakage and malicious side effects.

cs.AI↗

arXiv2025

Modeling Reachability Types with Logical Relations

Reachability types are a recent proposal to bring Rust-style reasoning about memory properties to higher-level languages, with a focus on higher-order functions, parametric types, and shared mutable state -- features that are only partially supported by current techniques as employed in Rust. While prior work has established key type soundness results for reachability types using the usual syntactic techniques of progress and preservation, stronger metatheoretic properties have so far been unexplored. This paper presents an alternative semantic model of reachability types using logical relations, providing a framework in which we study key properties of interest: (1) semantic type soundness, including of not syntactically well-typed code fragments, (2) termination, especially in the presence of higher-order state, (3) effect safety, especially the absence of observable mutation, and, finally, (4) program equivalence, especially reordering of non-interfering expressions for parallelization or compiler optimization.

cs.PL↗

arXiv2025

What's in the Box: Ergonomic and Expressive Capture Tracking over Generic Data Structures (Extended Version)

Capturing types in Scala unify static effect and resource tracking with object capabilities, enabling lightweight effect polymorphism with minimal notational overhead. However, their expressiveness has been insufficient for tracking capabilities embedded in generic data structures, preventing them from scaling to the standard collections library -- an essential prerequisite for broader adoption. This limitation stems from the inability to name capabilities within the system's notion of box types. This paper develops System Capless, a new foundation for capturing types that provides the theoretical basis for reach capabilities (rcaps), a novel mechanism for naming "what's in the box." The calculus refines the universal capability notion into a new scheme with existential and universal capture set quantification. Intuitively, rcaps witness existentially quantified capture sets inside the boxes of generic types in a way that does not require exposing existential capture types in the surface language. We have fully mechanized the formal metatheory of System Capless in Lean, including proofs of type soundness and scope safety. System Capless supports the same lightweight notation of capturing types plus rcaps, as certified by a type-preserving translation, and also enables fully optional explicit capture-set quantification to increase expressiveness. Finally, we present a full reimplementation of capture checking in Scala 3 based on System Capless and migrate the entire Scala collections library and an asynchronous programming library to evaluate its practicality and ergonomics. Our results demonstrate that reach capabilities enable the adoption of capture checking in production code with minimal changes and minimal-to-zero notational overhead in a vast majority of cases.

cs.PL↗

arXiv2023

Graph IRs for Impure Higher-Order Languages (Technical Report)

This is a companion report for the OOPSLA 2023 paper of the same title, presenting a detailed end-to-end account of the $λ^*_{\mathsf{G}}$ graph IR, at a level of detail beyond a regular conference paper. Our first concern is adequacy and soundness of $λ^*_{\mathsf{G}}$, which we derive from a direct-style imperative functional language (a variant of Bao et al.'s $λ^*$-calculus with reachability types and a simple effect system) by a series of type-preserving translations into a calculus in monadic normalform (MNF). Static reachability types and effects entirely inform $λ^*_{\mathsf{G}}$'s dependency synthesis. We argue for its adequacy by proving its functional properties along with dependency safety via progress and preservation lemmas with respect to a notion of call-by-value (CBV) reduction that checks the observed order of effects. Our second concern is establishing the correctness of $λ^*_{\mathsf{G}}$'s equational rules that drive compiler optimizations (e.g., DCE, $λ$-hoisting, etc.), by proving contextual equivalence using logical relations. A key insight is that the functional properties of dependency synthesis permit a logical relation on $λ^*_{\mathsf{G}}$ in MNF in terms of previously developed logical relations for the direct-style $λ^*$-calculus. Finally, we also include a longer version of the conference paper's section on code generation and code motion for $λ^*_{\mathsf{G}}$ as implemented in Scala~LMS.

cs.PL↗

arXiv2023

Polymorphic Reachability Types: Tracking Freshness, Aliasing, and Separation in Higher-Order Generic Programs

Reachability types are a recent proposal that has shown promise in scaling to higher-order but monomorphic settings, tracking aliasing and separation on top of a substrate inspired by separation logic. The prior $λ^*$ reachability type system qualifies types with sets of reachable variables and guarantees separation if two terms have disjoint qualifiers. However, naive extensions with type polymorphism and/or precise reachability polymorphism are unsound, making $λ^*$ unsuitable for adoption in real languages. Combining reachability and type polymorphism that is precise, sound, and parametric remains an open challenge. This paper presents a rethinking of the design of reachability tracking and proposes a solution to the key challenge of reachability polymorphism. Instead of always tracking the transitive closure of reachable variables as in the original design, we only track variables reachable in a single step and compute transitive closures only when necessary, thus preserving chains of reachability over known variables that can be refined using substitution. To enable this property, we introduce a new freshness qualifier, which indicates variables whose reachability sets may grow during evaluation steps. These ideas yield the simply-typed $λ^\diamond$-calculus with precise lightweight, i.e., quantifier-free, reachability polymorphism, and the $\mathsf{F}_{<:}^\diamond$-calculus with bounded parametric polymorphism over types and reachability qualifiers. We prove type soundness and a preservation of separation property in Coq.

cs.PL↗

arXiv2019

Type-safe, Polyvariadic Event Correlation

The pivotal role that event correlation technology plays in todays applications has lead to the emergence of different families of event correlation approaches with a multitude of specialized correlation semantics, including computation models that support the composition and extension of different semantics. However, type-safe embeddings of extensible and composable event patterns into statically-typed general-purpose programming languages have not been systematically explored so far. Event correlation technology has often adopted well-known and intuitive notations from database queries, for which approaches to type-safe embedding do exist. However, we argue in the paper that these approaches, which are essentially descendants of the work on monadic comprehensions, are not well-suited for event correlations and, thus, cannot without further ado be reused/re-purposed for embedding event patterns. To close this gap we propose PolyJoin, a novel approach to type-safe embedding for fully polyvariadic event patterns with polymorphic correlation semantics. Our approach is based on a tagless final encoding with uncurried higher-order abstract syntax (HOAS) representation of event patterns with n variables, for arbitrary $n \in \mathbb{N}$. Thus, our embedding is defined in terms of the host language without code generation and exploits the host language type system to model and type check the type system of the pattern language. Hence, by construction it impossible to define ill-typed patterns. We show that it is possible to have a purely library-level embedding of event patterns, in the familiar join query notation, which is not restricted to monads. PolyJoin is practical, type-safe and extensible. An implementation of it in pure multicore OCaml is readily usable.

cs.PL↗

arXiv2018

A Co-contextual Type Checker for Featherweight Java (incl. Proofs)

This paper addresses compositional and incremental type checking for object-oriented programming languages. Recent work achieved incremental type checking for structurally typed functional languages through co-contextual typing rules, a constraint-based formulation that removes any context dependency for expression typings. However, that work does not cover key features of object-oriented languages: Subtype polymorphism, nominal typing, and implementation inheritance. Type checkers encode these features in the form of class tables, an additional form of typing context inhibiting incrementalization. In the present work, we demonstrate that an appropriate co-contextual notion to class tables exists, paving the way to efficient incremental type checkers for object-oriented languages. This yields a novel formulation of Igarashi et al.'s Featherweight Java (FJ) type system, where we replace class tables by the dual concept of class table requirements and class table operations by dual operations on class table requirements. We prove the equivalence of FJ's type system and our co-contextual formulation. Based on our formulation, we implemented an incremental FJ type checker and compared its performance against javac on a number of realistic example programs.

cs.PL↗

arXiv2016

CPL: A Core Language for Cloud Computing -- Technical Report

Running distributed applications in the cloud involves deployment. That is, distribution and configuration of application services and middleware infrastructure. The considerable complexity of these tasks resulted in the emergence of declarative JSON-based domain-specific deployment languages to develop deployment programs. However, existing deployment programs unsafely compose artifacts written in different languages, leading to bugs that are hard to detect before run time. Furthermore, deployment languages do not provide extension points for custom implementations of existing cloud services such as application-specific load balancing policies. To address these shortcomings, we propose CPL (Cloud Platform Language), a statically-typed core language for programming both distributed applications as well as their deployment on a cloud platform. In CPL, application services and deployment programs interact through statically typed, extensible interfaces, and an application can trigger further deployment at run time. We provide a formal semantics of CPL and demonstrate that it enables type-safe, composable and extensible libraries of service combinators, such as load balancing and fault tolerance.

cs.PL↗