Capturing Overlapping, Triggered, and Preemptive Collaborations Using MSCs

Krüger, Ingolf H.

doi:10.1007/3-540-36578-8_27

Cited by 25 publications

(22 citation statements)

References 7 publications

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“…In this context [9] introduces a new composition operator called "trigger composition" to extend the expressiveness of MSCs for liveness/progress properties. This operator is equivalent to our OCL liveness template, consequently MSCs with trigger composition can be modelled with our liveness-enriched sequence diagrams.…”

Section: Conclusion and Related Workmentioning

confidence: 99%

Formalizing Liveness-Enriched Sequence Diagrams Using ASMs

Cavarra

Küster-Filipe

2004

Lecture Notes in Computer Science

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Abstract. In UML 2.0 sequence diagrams have been considerably extended, influenced by Live Sequence Charts (LSCs), a very expressive extension of Message Sequence Charts (MSC) with liveness. Nonetheless, fundamental liveness properties can still not be expressed in the new sequence diagrams. In recent work, we have proposed to solve this by enriching sequence diagrams with a simple but powerful Object Constraint Language (OCL) template for liveness. In this paper, we show how to formalize our liveness-enriched sequence diagrams using Abstract State Machines. Sequence diagrams still have several open problems. For example, the semantics of some of the newly introduced operators is ambiguous, and it is not clear how they can be used or combined with other operators. We address some of these issues in the paper. Finally, a further advantage of using ASMs as a semantic model concerns synthesis. It is our ultimate goal to be able to synthesise automatically a state-based object system from our richer sequence diagrams. ASMs are a state-based and operational formalism which therefore eases this task considerably.

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Section: Conclusion and Related Workmentioning

confidence: 99%

Formalizing Liveness-Enriched Sequence Diagrams Using ASMs

Cavarra

Küster-Filipe

2004

Lecture Notes in Computer Science

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“…Thus, our work is not aimed at discovering the complete behavior or APIs of certain components, but, rather, to capture the way components cooperate to implement certain system features. Indeed, inter-object scenarios are popular means to specify requirements (see, e.g., [15,19,21,38,39]). The addition of value-based invariants strengthens the expressive power of the mined scenarios.…”

Section: Related Workmentioning

confidence: 99%

Scenario-based and value-based specification mining: better together

Maoz

2012

Autom Softw Eng

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Specification mining takes execution traces as input and extracts likely program invariants, which can be used for comprehension, verification, and evolution related tasks. In this work we integrate scenario-based specification mining, which uses data-mining algorithms to suggest ordering constraints in the form of live sequence charts, an inter-object, visual, modal, scenario-based specification language, with mining of value-based invariants, which detects likely invariants holding at specific program points. The key to the integration is a technique we call scenario-based slicing, running on top of the mining algorithms to distinguish the scenario-specific invariants from the general ones. The resulting suggested specifications are rich, consisting of modal scenarios annotated with scenario-specific value-based invariants, referring to event parameters and participating object properties.An evaluation of our work over a number of case studies shows promising results in extracting expressive specifications from real programs, which could not be extracted previously. The more expressive the mined specifications, the higher their potential to support program comprehension and testing.

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“…We believe some of the ideas presented here may be adapted to accelerate execution and simulation of other variants of MSCs, see, e.g., [1,15].…”

Section: Related and Future Workmentioning

confidence: 99%

Accelerating Smart Play-Out

Harel

Kugler

Maoz

et al. 2010

SOFSEM 2010: Theory and Practice of Computer Science

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Abstract. Smart play-out is a method for executing declarative scenariobased specifications, which utilizes powerful computation methods to compute safe supersteps, thus helping to avoid violations that may be caused by naïve execution. Major challenges for smart play-out are performance and scalability. In this work we show how to accelerate smart play-out by adapting and applying ideas inspired by formal verification and compiler optimization. Specifically, we present an algorithm that can reduce the size of the specification considered for smart play-out, while maintaining soundness and completeness. Experimental results show significant performance improvements and thus open the way to the application of smart play-out to large scenario-based programs.

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Capturing Overlapping, Triggered, and Preemptive Collaborations Using MSCs

Cited by 25 publications

References 7 publications

Formalizing Liveness-Enriched Sequence Diagrams Using ASMs

Formalizing Liveness-Enriched Sequence Diagrams Using ASMs

Scenario-based and value-based specification mining: better together

Accelerating Smart Play-Out

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