Polymorphic scenario-based specification models: semantics and applications

Maoz, Shahar

doi:10.1007/s10270-010-0168-6

Cited by 4 publications

(2 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The principle idea behind multi-level modeling is to be able to retrieve type-and instance-level information individually and independently from one another, such that the abstraction can be dynamically chosen depending on the purpose of the model. Using scenarios, this was achieved in [26] by applying polymorphic scenario-based specification models in order to implement interfaces within instances. However, this requires sophisticated and unambiguous instance-level and type-level representations (see [27,28]).…”

Section: Multi-level Modeling and Abstraction On Type-and Instance-levelmentioning

confidence: 99%

“…In [33,34], a different definition for multi-level modeling is proposed, such as the meta-language defines the context by means of variability indicators from [34]. The benefit of this approach is that both ontological relationships (beyond the interfaceimplementation relationship from [26]) as well as classification of metaphysical structures [35,36] can be represented. This allows for modeling relationships between, but also within the same level of abstraction.…”

Section: Multi-level Modeling and Abstraction On Type-and Instance-levelmentioning

confidence: 99%

See 1 more Smart Citation

Multi-Level Message Sequence Charts to Validate the Collaborative Automotive Cyber-Physical Systems

Daun¹,

Tenbergen²,

Brings³

et al. 2021

JASEN

View full text Add to dashboard Cite

Autonomous driving and e-mobility are swiftly becoming not only the work of science fiction or popular science, but a reality.A key focus of manufacturers and suppliers in the automotive domain is of course to specify systems that implement this reality. Often, scenarios at type-level are used throughout the development process to specify system behavior and interaction within the car, as scenario models are comparatively easy to understand and can easily be subjected to manual validation. However, autonomous driving and e-mobility require interaction not just of systems within the same car, but collaboration between multiple cars as well as between cars and miscellaneous road infrastructure (e.g., smart road signs). The car becomes a Cyber-Physical System that dynamically forms collaborating networks at runtime with other Cyber-Physical System to create functionality that goes beyond the scope of the individual vehicle (e.g., resolve a traffic jam). Consequently, a plethora of possible compositions of such a network exist and must be specified and validated completely to assure their adequate and safe execution at runtime. Doing this at type-level with scenario models becomes prohibitively tedious, error prone, and likely results in unrealistic development cost. To combat this issue, we investigate the use of multi-level Message Sequence Charts to allow for specifying interaction scenarios between collaborative Cyber-Physical System in a network of collaborating automotive Cyber-Physical System. To assist the developer in systematically defining multi-level Message Sequence Charts, we propose two processes. The resulting diagrams use a mixture of type and instance-level abstractions within one conceptual diagram. This allows reducing the required effort to manually validate the adequacy of scenarios to a manageable amount because information within the scenarios can be validated in batches. At the same time, instance-level defects become more obvious. Evaluation results from a controlled experiment show that multi-level Message Sequence Charts contribute to effectiveness and efficiency of manual validation for collaborative automotive Cyber-Physical System.

show abstract

Section: Multi-level Modeling and Abstraction On Type-and Instance-levelmentioning

confidence: 99%

Section: Multi-level Modeling and Abstraction On Type-and Instance-levelmentioning

confidence: 99%

Multi-Level Message Sequence Charts to Validate the Collaborative Automotive Cyber-Physical Systems

Daun¹,

Tenbergen²,

Brings³

et al. 2021

JASEN

View full text Add to dashboard Cite

show abstract

Semantically Configurable Analysis of Scenario-Based Specifications

Barak

Maoz

2014

Fundamental Approaches to Software Engineering

Self Cite

View full text Add to dashboard Cite

Abstract. Scenarios, represented using variants of sequence diagrams, are popular means to specify systems requirements. Live sequence charts (LSC), is a formal and expressive scenario-based specification language, which has been extensively studied over the last decade. Careful reading of the LSC literature, however, reveals many variations and ambiguities in the semantics of LSC, as it is used by different authors in different contexts. Moreover, different works define their semantics of LSC using different means. This variability, in both language features and means of semantics definition, creates a challenge for researchers and tool developers.In this paper we address this challenge by investigating semantically configurable analysis. We define and formalize the variability in the semantics of LSC using a feature model and develop an analysis technique that can be instantiated to comply with each of its legal configurations. Thus, the analysis is semantically configured and its results change according to the semantics induced by the selected feature configuration. The work is implemented and demonstrated using examples. It advances the state-of-the-art in the area of scenario-based specifications and provides an example for a formal and automated approach to handling semantic variability in modeling languages. ". . . the world don't move to the beat of just one drum. . . "Diff 'rent Strokes (1978)

show abstract