A Formal Machine–Learning Approach to Generating Human–Machine Interfaces From Task Models

Li, Meng; Wei, Jiajun; Zheng, Xi; Bolton, Matthew L.

doi:10.1109/thms.2017.2700630

Cited by 22 publications

(6 citation statements)

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“…Navarre et al [30] propose a framework for analysing the interactive systems, particularly for the combined behaviour of user task models and system models to check whether a user task is supported by the system model. [27] describes an approach for generating formal designs of HMI behaviour from task-analysis models and then the results are demonstrated through different case studies. [17] presents the use of formal techniques for the analysis of human-machine interactions.…”

Section: Discussionmentioning

confidence: 99%

Refinement Based Formal Development of Human-Machine Interface

Geniet

Singh

2018

Software Technologies: Applications and Foundations

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Human factors have been considered as the most common causes of accidents, particularly for interacting with complex critical systems related to avionics, railway, nuclear and medical domains. Mostly, a human-machine interface (HMI) is developed independently and the correctness of possible interactions is heavily dependent on testing, which cannot guarantee the absence of runtime errors. The use of formal methods in HMI development may assure such guarantee. This paper presents a methodology for developing an HMI using a correct by construction approach, which allows us to introduce the HMI components, functional behaviour and the required safety properties progressively. The proposed methodology, generic refinement strategy, supports a development of the model-view-controller (MVC) architecture. The whole approach is formalized using Event-B and relies on the Rodin tools to check the internal consistency with respect to the given safety properties, invariants and events. Finally, an industrial case study is used to illustrate the effectiveness of our proposed approach for developing an HMI.

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Section: Discussionmentioning

confidence: 99%

Refinement Based Formal Development of Human-Machine Interface

Geniet

Singh

2018

Software Technologies: Applications and Foundations

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“…This allowed us to use EOFM's translator for incorporating task behavior in a formal system model. This also allowed us to use EOFM's support for automatically creating (Li, Wei, Zheng, & Bolton, 2017) the other formal elements of the system. To create tests, we used the automated test case generator of SAL (Hamon et al, 2004).…”

Section: Methods Implementationmentioning

confidence: 99%

“…Using this task as input, we created a functional design of the system's interface using the generation method described by Li et al (2017). This produced the interface model shown in Figure 4.…”

Section: Applicationmentioning

confidence: 99%

Task-based Automated Test Case Generation for Human-machine Interaction

Bolton

2019

Proceedings of the Human Factors and Ergonomics Society Annual

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Testing is an effective approach for finding discrepancies between intended and actual system behavior. However, the complexity of modern system can make it difficult for analysts to anticipate all the interactions that need to be tested. This is particularly true for human-interactive systems where humans may do things that were not anticipated by analysts. We address this by introducing a novel approach to automated test case generation for human-machine interaction. We do this by combining formal models of human-machine interfaces with formal models of human task behavior. We then use the robust search capabilities of model checking to generate test sequences guaranteed to satisfy test coverage criteria. We demonstrate the capabilities of our approach with of a pod-based coffee machine. Results and future research are discussed.

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“…Ref. [21] discusses about user-centered design (UCD), an approach for creating human-machine interfaces that are usable and support the human operator’s tasks. Formal methods are tools that enable analysts to consider all of the possible system interactions using a combination of formal modeling, specification, and proof-based verification.…”

Section: Related Workmentioning

confidence: 99%

An IoT Surveillance System Based on a Decentralised Architecture

Santamaria

Raimondo

Tropea

et al. 2019

Sensors

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In the last few years, we witnessed numerous episodes of terrorist attacks and menaces in public crowded places. The necessity of better surveillance in these places pushed the development of new automated solutions to spot and notify possible menaces as fast as possible. In this work, we propose a novel approach to create a decentralized architecture to manage patrolling drones and cameras exploiting lightweight protocols used in the internet of things (IoT) domain. Through the adoption of the mist computing paradigm it is possible to give to all the object of the smart ecosystem a cognitive intelligence to speed up the recognition and analysis tasks. Distributing the intelligence among all the objects of the surveillance ecosystem allows a faster recognition and reaction to possible warning situations. The recognition of unusual objects in certain areas, e.g., airports, train stations and bus stations, has been made using computer vision algorithms. The adoption of the IoT protocols in a hierarchical architecture provides high scalability allowing an easy and painless join of other smart objects. Also a study on the soft real-time feasibility has been conducted and is herein presented.

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A Formal Machine–Learning Approach to Generating Human–Machine Interfaces From Task Models

Cited by 22 publications

References 58 publications

Refinement Based Formal Development of Human-Machine Interface

Refinement Based Formal Development of Human-Machine Interface

Task-based Automated Test Case Generation for Human-machine Interaction

An IoT Surveillance System Based on a Decentralised Architecture

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