arrow
Return

Towards Lightweight and Efficient Choreographic Cloud Services

delete2026-01-01
delete0
PRE
AI
A
Alex Ionescu *
A
Alejandro Russo
DOI:10.1145/3779209.3779537delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Choreographic programming provides a high-level abstraction for writing distributed computations while ensuring deadlock-freedom by construction. HasChor, a Haskell-based choreographic programming framework, offers a practical implementation of these ideas but faces limitations in handling an arbitrary number of participants and optimizing the communication of branches. In this work, we introduce CloudChor, a set of extensions that enhance HasChor's expressiveness and efficiency through the use of multiply-located values, allowing choreographies to distribute and collect data across multiple participants in a structured manner. Additionally, we refine HasChor's branching mechanism through a lightweight static analysis, selectively propagating branching decisions only to relevant participants, reducing communication overhead. To strengthen theoretical guarantees, we establish a formal semantics for HasChor and our extensions, proving deadlock-freedom. Finally, we demonstrate the practicality of our enhancements by implementing a data clean room protocol using CloudChor. Our contributions improve the applicability of choreographic programming to cloud-based secure data collaborations, making it a stronger candidate for real-world deployments.
Keywords:
Choreographic programming
Generic programming
Haskell
Distributed systems
Data clean rooms

Journal

P
PROCEEDINGS OF THE 2026 ACM SIGPLAN INTERNATIONAL WORKSHOP ON PARTIAL EVALUATION AND PROGRAM MANIPULATION, PEPM 2026
IF:
0
Papers:
5
Citations:
0

Organization

C
chalmers university of technology
Scholars:
1.5W
Papers: 1.6W
Citations: 10