Implementing Joins Using Extensible Pattern Matching

Haller, Philipp; Cutsem, Tom Van

doi:10.1007/978-3-540-68265-3_9

Cited by 30 publications

(38 citation statements)

References 20 publications

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“…Fournet and Gonthier briefly describe an extension of the join calculus with partial failure and remote failure detection [21]. The aspect join calculus can also serve as a basis to implement concurrent and distributed aspects in other languages for which a variant of the join calculus has been developed, such as Cω [6] and Scala Joins [26]. Another interesting perspective is to study the application of aspects in chemical engines for Cloud computing.…”

Section: Discussionmentioning

confidence: 99%

“…5 This paper develops the formal foundations of distributed AOP using a chemical calculus, essentially a variant of the distributed join calculus [22]. The join calculus is a functional name-passing calculus based on the chemical abstract machine and implemented in several mainstream languages like OCaml [24], C# [6] and Scala [26]. Chemical execution engines are also being developed for Cloud computing [45,40].…”

Section: Introductionmentioning

confidence: 99%

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Chemical foundations of distributed aspects

Tabareau

Tanter

2018

Distrib. Comput.

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Distributed applications are challenging to program because they have to deal with a plethora of concerns, including synchronization, locality, replication, security and fault tolerance. Aspect-oriented programming (AOP) is a paradigm that promotes better modularity by providing means to encapsulate crosscutting concerns in entities called aspects. Over the last years, a number of distributed aspect-oriented programming languages and systems have been proposed, illustrating the benefits of AOP in a distributed setting.Chemical calculi are particularly well-suited to formally specify the behavior of concurrent and distributed systems. The join calculus is a functional name-passing calculus, with both distributed and object-oriented extensions. It is used as the basis of concurrency and distribution features in several mainstream languages like C# (Polyphonic C#, now Cω), OCaml (JoCaml), and Scala Joins. Unsurprisingly, practical programming in the join calculus also suffers from modularity issues when dealing with crosscutting concerns.We propose the Aspect Join Calculus, an aspectoriented and distributed variant of the join calculus that addresses crosscutting and provides a formal foundation for distributed AOP. We develop a minimal aspect join calculus that allows aspects to advise chemical reactions. We show how to deal with causal relations in pointcuts and how to support advanced customizable aspect weaving semantics. We also provide the foun-N. Tabareau

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Chemical foundations of distributed aspects

Tabareau

Tanter

2018

Distrib. Comput.

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“…In practice, one could implement a default FIFO behavior, or allow the programmer to specify the scheduling algorithm [7,9,10]. Join patterns [17,4,18] could also be introduced as a scheduling and synchronization mechanism for incoming messages. Regarding coordination of tasks, in the presented model, tasks are activated nondeterministically when they are ready.…”

Section: Discussionmentioning

confidence: 99%

CoBoxes: Unifying Active Objects and Structured Heaps

Schäfer

Poetzsch-Heffter

2008

Lecture Notes in Computer Science

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Abstract. Concurrent programming in object-oriented languages is a notoriously difficult task. We propose coboxes -a novel language concept which combines and generalizes active objects and techniques for heap structuring. CoBoxes realize a data-centric approach that guarantees mutual-exclusion for groups of objects. This is important for more complex data structures with invariants ranging over several objects. CoBoxes support multiple entry objects, several cooperating tasks in a cobox, and nesting of coboxes for composition and internal parallelism. Communication between coboxes is handled by asynchronous method calls with futures, which is in particular suitable for distributed programming. In this paper, we explain how aspects of concurrent programming can be solved by coboxes. We develop a core language for coboxes and present a formal operational semantics for this language.

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“…Second generation join languages (e.g., JErlang [16]) support n-ary predicates but no streams. Scala Joins [3] are special, isolated, case of predicated join language supporting only intra-event conditions ( 1, #, 1 ). Generic correlation #, #, # .…”

Section: State Of the Art Of Cedmentioning

confidence: 99%

Scalable Efficient Composite Event Detection

Jayaram

Eugster

2010

Lecture Notes in Computer Science

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Abstract. Composite event detection (CED) is the task of identifying combinations of events which are meaningful with respect to programdefined patterns. Recent research in event-based programming has focused on language design (in different paradigms), leading to a wealth of prototype programming models and languages. However, implementing CED in an efficient and scalable manner remains an under-addressed problem. In fact, the lack of scalable algorithms is the main roadblock to incorporating support for more expressive event patterns into prominent event-based programming languages. This lack of scalable algorithms is a particularly acute problem in event stream processing, where event patterns can additionally be specified over time windows. In this paper we describe GenTrie, a deterministic trie-based algorithm for CED. We describe how complex event patterns are split, how each sub-pattern maps to a node in the trie, and demonstrate through empirical evaluation that GenTrie has higher throughput than current implementations of related languages.

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Implementing Joins Using Extensible Pattern Matching

Cited by 30 publications

References 20 publications

Chemical foundations of distributed aspects

Chemical foundations of distributed aspects

CoBoxes: Unifying Active Objects and Structured Heaps

Scalable Efficient Composite Event Detection

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