3 research outputs found
Analysing and Demonstrating Tool-Supported Customizable Task Notations
International audienceWhen task descriptions are precise they can be analysed to yield a variety of insights about interaction, such as the quantity of actions performed, the amount of information that must be perceived, and the cognitive workload involved. Task modelling notations and associated tools provide support for precise task description, but they generally provide a fixed set of constructs, which can limit their ability to model new and evolving application domains and technologies. This article describes challenges involved in using fixed notations for describing tasks. We use examples of recognized tasks analysis processes and their phases to show the need for customization of task notations, and through a series of illustrative examples, we demonstrate the benefits using our extensible task notation and tool (HAMSTERS-XL)
Engineering Annotations: A Generic Framework For Gluing Design Artefacts in Models of Interactive Systems
International audienceAlong the design process of interactive system many intermediate artefacts (such as user interface prototypes, task models describing user work and activities, dialog models specifying system behavior, interaction models describing user interactions …) are created, tested, revised and improved until the development team produces a validated version of the full-fledged system. Indeed, to build interactive systems there is a need to use multiple artefacts/models (as they provide a complementary view). However, relevant information for describing the design solution and/or supporting design decisions (such as rational about the design, decisions made, recommendations, etc.) is not explicitly capturable in the models/artefacts, hence the need for annotations. Multi-artefacts approaches usually argue that a given information should only be present in one artefact to avoid duplication and increase maintainability of the artefacts. Nonetheless, annotations created on one artefact are usually relevant to other artefacts/models. So that, there is a need for tools and techniques to coordinate annotations across artefacts/models which is the contribution of the present work. In this paper, we propose a model-based approach that was conceived to handle annotations in a systematic way along the development process of interactive systems. As part of the solution, we propose an annotation model built upon the W3C's Web Annotation Data Model. The feasibility of the approach is demonstrated by means of a tool suite featuring a plugin, which has been deployed and tested over the multi-artefacts. The overall approach is illustrated on the design of an interactive cockpit application performing two design iterations. The contribution brings two main benefits for interactive systems engineering: i) it presents a generic pattern for integrating information in multiple usually heterogenous artefacts throughout the design process of interactive systems; and ii) it highlights the need for tools helping to rationalize and to document the various artefacts and the related decisions made during interactive systems design. CCS CONCEPTS • Human-centered computing • Human computer interaction (HCI
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Addressing Resource Variability Through Resource-Driven Adaptation
Software systems execute tasks that depend on different types of resources. However, the variability of resources may interfere with the ability of software systems to execute important tasks. Resource variability can occur due to several reasons including unexpected hardware failures, excess workloads, or lack of materials. For example, in automated warehouses, malfunctioning robots could delay product deliveries causing customer dissatisfaction and, therefore, reducing an enterprise’s sales. Moreover, the unavailability of medical materials hinders the ability of hospitals to perform medically-critical operations causing loss of life. In this thesis, we propose to address the problem of resource variability through resource-driven adaptation, using task models as input for adaptation decisions. The thesis presents the following contributions:
• SPARK: a framework for performing proactive and reactive resource-driven adaptation based on multiple task-related criteria. The framework supports different types of depletable and reusable resources that could face variability. SPARK assists with four types of adaptation, namely: (i) execution of a similar task that requires fewer resources, (ii) substitution of resources by alternative ones, (iii) execution of tasks in a different order, and (iv) cancellation of the execution of tasks.
• SERIES: a task modelling notation and editor tool that enables software practitioners to create task models that serve as input for SPARK. SERIES supports the representation of task priorities, task variants, task execution types, resource types, and properties representing users’ feedback.
SPARK was evaluated in terms of the percentage of executed critical task requests, the average criticality of the executed task requests in comparison to the non-executed ones, overhead, and scalability through two case studies concerned with a medicine consumption system and a manufacturing system. The results of the evaluation showed that SPARK increased the number of executed critical task requests during resource variability. Additionally, the results showed that the time it takes to prepare and apply adaptation plans does not add significant overhead that hinders the ability of software systems to execute tasks in a tolerable waiting time. Furthermore, SPARK was shown to be scalable since the abovementioned time increases polynomially relative to the input size (number of tasks and task variants).
SERIES was evaluated through a user study with twenty software practitioners. The results showed that software practitioners performed very well when explaining and creating task models using SERIES. These results were reflected in the task modelling activities that the participants performed as well as in their positive feedback regarding the usability of SERIES and the clarity of its semantic constructs.
Overall, we conclude that the research presented in the thesis contributes to addressing resource variability through resource-driven adaptation. We also provide suggestions for future work that can extend this research