A Concept for Testing Robustness and Safety of the Context-Aware Behaviour of Autonomous Systems

Micskei, Zoltán; Szatmári, Zoltán; Oláh, János; Majzik, István

doi:10.1007/978-3-642-30947-2_55

Cited by 40 publications

(44 citation statements)

References 6 publications

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“…This is, in fact, very useful in test generation [40] or quick fix generation purposes. Below we only briefly demonstrate how to derive a valid model of minimal size (see Figure 19) which contains all PSs from Figure 8.…”

Section: Model Generation For Partial Snapshotsmentioning

confidence: 99%

Formal validation of domain-specific languages with derived features and well-formedness constraints

et al. 2015

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Despite the wide range of existing tool support, constructing a design environment for a complex domain-specific language (DSL) is still a tedious task as the large number of derived features and well-formedness constraints complementing the domain metamodel necessitate special handling. Such derived features and constraints are frequently defined by declarative techniques (such graph patterns or OCL invariants).However, for complex domains, derived features and constraints can easily be formalized incorrectly resulting in inconsistent, incomplete or ambiguous DSL specifications. To detect such issues, we propose an automated mapping of EMF metamodels enriched with derived features and well-formedness constraints captured as graph queries in EMF-IncQuery or (a subset of) OCL invariants into an effectively propositional fragment of first-order logic which can be efficiently analyzed by back-end reasoners.On the conceptual level, the main added value of our encoding is (1) to transform graph patterns of the EMF-IncQuery framework into FOL and (2) to introduce approximations for complex language features (e.g. transitive closure or multiplicities) which are not expressible in FOL. On the practical level, we identify and address relevant challenges and scenarios for systematically validating DSL specifications. Our approach is supported by a tool and it will be illustrated on analyzing a DSL in the avionics domain. We also present initial performance experiments for the validation using Z3 and Alloy as back-end reasoners.

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Section: Model Generation For Partial Snapshotsmentioning

confidence: 99%

Formal validation of domain-specific languages with derived features and well-formedness constraints

et al. 2015

Self Cite

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“…Similar definitions are provided by (Micskei, Szatmári, Oláh, & Majzik, 2012) who write that "notable characteristics shared by the different kinds of autonomous systems include reasoning, learning, adaptation and context-awareness" and others such as (Watson & Scheidt, 2005) and (Brat & Jonsson, 2005). Of course not all autonomous systems exhibit the same level of autonomy.…”

Section: Autonomous Systemsmentioning

confidence: 88%

“… Complex environment: The larger size and higher complexity of the valid input space and the context in which the system operates, both of which might be partially unknown at design time. This makes exhaustive testing -as it is done traditionally -impossible (Brat & Jonsson, 2005), (Schumann & Visser, 2006), (Clapper, Young, Cartwright, & Grimes, 2007), (Micskei, Szatmári, Oláh, & Majzik, 2012), (Brun, 2009) and (Pouly & Jouanneau, 2012).…”

Section: Challenges For Testing Autonomous Systemsmentioning

confidence: 99%

Testing of Autonomous Systems – Challenges and Current State‐of‐the‐Art

Helle

Schamai

Strobel

2016

INCOSE International Symp

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Autonomous systems are on the rise. However, the challenge to test autonomous systems to ensure their safe and fault‐free behaviour is not solved yet. This is especially critical when we consider the fact that autonomous systems are often safety‐critical systems envisaged to interact with humans without explicit human supervision. This paper points out why testing autonomous systems is such a challenge and provides an overview of the current state‐of‐the‐art theory and practice. The gathered information is then condensed into guiding points for the way forward.

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“…Modelling environments may provide validation for the system under design from an early stage of development with efficient tool support for checking wellformedness (WF) constraints and design rules over large model instances of the DSL using tools like Eclipse OCL [24] or graph queries [41]. Model generation techniques [16,19,35,39] are able to automatically provide a range of solution candidates for allocation problems [19], model refactoring or context generation [21]. Finally, models can be processed by query-based transformations or code generators to automatically synthesize source code or other artifacts.…”

Section: Introductionmentioning

confidence: 99%

Iterative Generation of Diverse Models for Testing Specifications of DSL Tools

Semeráth

Varró

2018

Fundamental Approaches to Software Engineering

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The validation of modeling tools of custom domain-specific languages (DSLs) frequently relies upon an automatically generated set of models as a test suite. While many software testing approaches recommend that this test suite should be diverse, model diversity has not been studied systematically for graph models. In the paper, we propose diversity metrics for models by exploiting neighborhood shapes as abstraction. Furthermore, we propose an iterative model generation technique to synthesize a diverse set of models where each model is taken from a different equivalence class as defined by neighborhood shapes. We evaluate our diversity metrics in the context of mutation testing for an industrial DSL and compare our model generation technique with the popular model generator Alloy.

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A Concept for Testing Robustness and Safety of the Context-Aware Behaviour of Autonomous Systems

Cited by 40 publications

References 6 publications

Formal validation of domain-specific languages with derived features and well-formedness constraints

Formal validation of domain-specific languages with derived features and well-formedness constraints

Testing of Autonomous Systems – Challenges and Current State‐of‐the‐Art

Iterative Generation of Diverse Models for Testing Specifications of DSL Tools

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