Demo Data from VLDB 2026 / reviewers in the wild / expert
Luke Cheeseman
dblp:362/6111
· DBLP profile ↗
2ranked-venue papers
2as first author
2since 2021 · last 2026
0009-0000-0632-9825ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021Theory of computation · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Concurrent programming · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Concurrent programming
concurrency models |
0.7 | 1 | 2023 | When Concurrency Matters: Behaviour-Oriented Concurrency · Proc. ACM Program. Lang. 2023 |
Methods — techniques the papers use, named apart from their topics
formal operational semantics · 0.7c++ runtime · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | When Behaviours Have to Happen: An Axiomatic Model of Causality in Behaviour-Oriented ConcurrencyabstractBehaviour-oriented concurrency (BoC) is a recently established programming model in which programmers define concurrent operations that execute atomically across multiple isolated resources. This allows for expressive interactions but introduces complex causal dependencies determined by dynamic resource overlap. Previous work defines the causal guarantees of BoC operationally, but mixes intended design constraints with incidental implementation details, leading to unintended causal orders. BoC is now being implemented across multiple languages and runtimes, all relying on the operational descriptions of causality. This paper develops an axiomatic model of BoC executions that makes the intrinsic orders explicit and derives the intended causal relation from their interaction. Using a set of representative programs and candidate executions, we motivate the design of this causal relation. We then prove that a representative minimal core calculus for BoC is sound with respect to this axiomatic model. Together, these results provide an implementation-independent foundation for reasoning about BoC causality across runtimes, schedulers and optimisation decisions. Luke Cheeseman, Elias Castegren, Tobias Wrigstad, Sophia Drossopoulou, Matthew J. Parkinson |
CONCUR | 1 |
| 2023 | When Concurrency Matters: Behaviour-Oriented ConcurrencyabstractExpressing parallelism and coordination is central for modern concurrent programming. Many mechanisms exist for expressing both parallelism and coordination. However, the design decisions for these two mechanisms are tightly intertwined. We believe that the interdependence of these two mechanisms should be recognised and achieved through a single, powerful primitive. We are not the first to realise this: the prime example is actor model programming, where parallelism arises through fine-grained decomposition of a program’s state into actors that are able to execute independently in parallel. However, actor model programming has a serious pain point: updating multiple actors as a single atomic operation is a challenging task. We address this pain point by introducing a new concurrency paradigm: Behaviour-Oriented Concurrency (BoC). In BoC, we are revisiting the fundamental concept of a behaviour to provide a more transactional concurrency model. BoC enables asynchronously creating atomic and ordered units of work with exclusive access to a collection of independent resources. In this paper, we describe BoC informally in terms of examples, which demonstrate the advantages of exclusive access to several independent resources, as well as the need for ordering. We define it through a formal model. We demonstrate its practicality by implementing a C++ runtime. We argue its applicability through the Savina benchmark suite: benchmarks in this suite can be more compactly represented using BoC in place of Actors, and we observe comparable, if not better, performance. Luke Cheeseman, Matthew J. Parkinson, Sylvan Clebsch, Marios Kogias, Sophia Drossopoulou, David Chisnall, Tobias Wrigstad, Paul Liétar |
Proc. ACM Program. Lang. | 1 |