Causal Closure for MSC Languages

Adsul, Bharat; Mukund, Madhavan; Kumar, K. Narayan; Narayanan, Vasumathi K.

doi:10.1007/11590156_27

Cited by 18 publications

(8 citation statements)

References 15 publications

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“…8), but the complexity is still exponential (the starting point there is a monoid homomorphism in place of an automaton). Our construction also reduces the complexity of other works [12,15] using Zielonka's theorem or its variant for communicating processes [1,13,7] to produce a distributed automaton with local final states or without deadlock. Very recently, [2] proposed a construction of non-deterministic asynchronous automata of size |A| 2 |Σ| while we produce a deterministic one.…”

Section: Introductionmentioning

confidence: 93%

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Constructing Exponential-Size Deterministic Zielonka Automata

Genest¹,

Muscholl²

2006

Automata, Languages and Programming

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Abstract. The well-known algorithm of Zielonka describes how to transform automatically a sequential automaton into a deterministic asynchronous trace automaton. In this paper, we improve the construction of deterministic asynchronous automata from finite state automaton. Our construction improves the well-known construction in that the size of the asynchronous automaton is simply exponential in both the size of the sequential automaton and the number of processes. In contrast, Zielonka's algorithm gives an asynchronous automaton that is doubly exponential in the number of processes (and simply exponential in the size of the automaton).

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Section: Introductionmentioning

confidence: 93%

“…This result is all the more fundamental since it has been used for several other closely related problems, as synthesis of communicating automata, with bounded communication channels [13,7,8], or existentially-bounded channels [6] or causal memory [1].…”

Section: Introductionmentioning

confidence: 99%

Constructing Exponential-Size Deterministic Zielonka Automata

Genest¹,

Muscholl²

2006

Automata, Languages and Programming

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“…In DSS there is lack of a centralized control and components have a restricted view [2,4]. Consequently, they may start with one scenario of the system and continue in another scenario in a shared state [29][30][31]. This state in some researches is referred to as identical states [1].…”

Section: Emergent Behavior and Emergent Behavior Detection Approachesmentioning

confidence: 99%

Detecting distributed software components that will not cause emergent behavior in asynchronous communication style

Fard

Far

2013

2013 IEEE 14th International Conference on Information Reuse &Amp; Integration (IRI)

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In distributed software systems (DSS) the functionality and/or control are distributed. This may cause the DSS components to show an unexpected behavior known as emergent behavior in the run time, which was not seen in their requirements and design. Emergent behaviors can have irreparable damages for companies. The savings in cost of detecting and fixing emergent behaviors in early phases is more than 20 times compared to fixing them after the deployment. The detecting methodologies usually utilize behavioral modeling which can face to state space explosion problem for large scale systems. Therefore, we approach this problem by detecting components that will not show emergent behavior and remove them from further analysis to help the scalability of these approaches. Previously, we have devised and implemented the algorithm for synchronous communications. In this paper, the extension of our method for detecting these components in the asynchronous communication style is presented which is closer to the real-world systems. The details of the technique and related algorithms are discussed.

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“…There are other interesting classes of learnable MPA, and our setting applies to the causal closure by Adsul et al [1]. We plan to provide high-level MSCs as a means to predefine patterns of positive or negative examples.…”

Section: Future Workmentioning

confidence: 99%

Replaying Play In and Play Out: Synthesis of Design Models from Scenarios by Learning

Bollig

Katoen

Kern

et al. 2007

Tools and Algorithms for the Construction and Analysis of Systems

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Abstract. This paper is concerned with bridging the gap between requirements, provided as a set of scenarios, and conforming design models. The novel aspect of our approach is to exploit learning for the synthesis of design models. In particular, we present a procedure that infers a message-passing automaton (MPA) from a given set of positive and negative scenarios of the system's behavior provided as message sequence charts (MSCs). The paper investigates which classes of regular MSC languages and corresponding MPA can (not) be learned, and presents a dedicated tool based on the learning library LearnLib that supports our approach.

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Causal Closure for MSC Languages

Cited by 18 publications

References 15 publications

Constructing Exponential-Size Deterministic Zielonka Automata

Constructing Exponential-Size Deterministic Zielonka Automata

Detecting distributed software components that will not cause emergent behavior in asynchronous communication style

Replaying Play In and Play Out: Synthesis of Design Models from Scenarios by Learning

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