14,058 research outputs found

    Intangible trust requirements - how to fill the requirements trust "gap"?

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    Previous research efforts have been expended in terms of the capture and subsequent instantiation of "soft" trust requirements that relate to HCI usability concerns or in relation to "hard" tangible security requirements that primarily relate to security a ssurance and security protocols. Little direct focus has been paid to managing intangible trust related requirements per se. This 'gap' is perhaps most evident in the public B2C (Business to Consumer) E- Systems we all use on a daily basis. Some speculative suggestions are made as to how to fill the 'gap'. Visual card sorting is suggested as a suitable evaluative tool; whilst deontic logic trust norms and UML extended notation are the suggested (methodologically invariant) means by which software development teams can perhaps more fully capture hence visualize intangible trust requirements

    Designing and evaluating the usability of a machine learning API for rapid prototyping music technology

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    To better support creative software developers and music technologists' needs, and to empower them as machine learning users and innovators, the usability of and developer experience with machine learning tools must be considered and better understood. We review background research on the design and evaluation of application programming interfaces (APIs), with a focus on the domain of machine learning for music technology software development. We present the design rationale for the RAPID-MIX API, an easy-to-use API for rapid prototyping with interactive machine learning, and a usability evaluation study with software developers of music technology. A cognitive dimensions questionnaire was designed and delivered to a group of 12 participants who used the RAPID-MIX API in their software projects, including people who developed systems for personal use and professionals developing software products for music and creative technology companies. The results from the questionnaire indicate that participants found the RAPID-MIX API a machine learning API which is easy to learn and use, fun, and good for rapid prototyping with interactive machine learning. Based on these findings, we present an analysis and characterization of the RAPID-MIX API based on the cognitive dimensions framework, and discuss its design trade-offs and usability issues. We use these insights and our design experience to provide design recommendations for ML APIs for rapid prototyping of music technology. We conclude with a summary of the main insights, a discussion of the merits and challenges of the application of the CDs framework to the evaluation of machine learning APIs, and directions to future work which our research deems valuable

    Modeling of system knowledge for efficient agile manufacturing : tool evaluation, selection and implementation scenario in SMEs

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    In the manufacturing world, knowledge is fundamental in order to achieve effective and efficient real time decision making. In order to make manufacturing system knowledge available to the decision maker it has to be first captured and then modelled. Therefore tools that provide a suitable means for capturing and representation of manufacturing system knowledge are required in several types of industrial sectors and types of company’s (large, SME). A literature review about best practice for capturing requirements for simulation development and system knowledge modeling has been conducted. The aim of this study was to select the best tool for manufacturing system knowledge modelling in an open-source environment. In order to select this tool, different criteria were selected, based on which several tools were analyzed and rated. An exemplary use case was then developed using the selected tool, Systems Modeling Language (SysML). Therefore, the best practice has been studied, evaluated, selected and then applied to two industrial use cases by the use of a selected opens source tool.peer-reviewe

    Lights, Camera, Action! Exploring Effects of Visual Distractions on Completion of Security Tasks

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    Human errors in performing security-critical tasks are typically blamed on the complexity of those tasks. However, such errors can also occur because of (possibly unexpected) sensory distractions. A sensory distraction that produces negative effects can be abused by the adversary that controls the environment. Meanwhile, a distraction with positive effects can be artificially introduced to improve user performance. The goal of this work is to explore the effects of visual stimuli on the performance of security-critical tasks. To this end, we experimented with a large number of subjects who were exposed to a range of unexpected visual stimuli while attempting to perform Bluetooth Pairing. Our results clearly demonstrate substantially increased task completion times and markedly lower task success rates. These negative effects are noteworthy, especially, when contrasted with prior results on audio distractions which had positive effects on performance of similar tasks. Experiments were conducted in a novel (fully automated and completely unattended) experimental environment. This yielded more uniform experiments, better scalability and significantly lower financial and logistical burdens. We discuss this experience, including benefits and limitations of the unattended automated experiment paradigm

    Evaluation of formal IDEs for human-machine interface design and analysis: the case of CIRCUS and PVSio-web

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    Critical human-machine interfaces are present in many systems including avionics systems and medical devices. Use error is a concern in these systems both in terms of hardware panels and input devices, and the software that drives the interfaces. Guaranteeing safe usability, in terms of buttons, knobs and displays is now a key element in the overall safety of the system. New integrated development environments (IDEs) based on formal methods technologies have been developed by the research community to support the design and analysis of high-confidence human-machine interfaces. To date, little work has focused on the comparison of these particular types of formal IDEs. This paper compares and evaluates two state-of-the-art toolkits: CIRCUS, a model-based development and analysis tool based on Petri net extensions, and PVSio-web, a prototyping toolkit based on the PVS theorem proving system.This work is partially supported by: Project NORTE-01-0145-FEDER-000016, financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF); Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) PhD scholarship

    A method for tailoring the information content of a software process model

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    The framework is defined for a general method for selecting a necessary and sufficient subset of a general software life cycle's information products, to support new software development process. Procedures for characterizing problem domains in general and mapping to a tailored set of life cycle processes and products is presented. An overview of the method is shown using the following steps: (1) During the problem concept definition phase, perform standardized interviews and dialogs between developer and user, and between user and customer; (2) Generate a quality needs profile of the software to be developed, based on information gathered in step 1; (3) Translate the quality needs profile into a profile of quality criteria that must be met by the software to satisfy the quality needs; (4) Map the quality criteria to set of accepted processes and products for achieving each criterion; (5) Select the information products which match or support the accepted processes and product of step 4; and (6) Select the design methodology which produces the information products selected in step 5

    Practical Strategies for Integrating a Conversation Analyst in an Iterative Design Process

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    We present a case study of an iterative design process that includes a conversation analyst. We discuss potential benefits of conversation analysis for design, and we describe our strategies for integrating the conversation analyst in the design process. Since the analyst on our team had no previous exposure to design or engineering, and none of the other members of our team had any experience with conversation analysis, we needed to build a foundation for our interaction. One of our key strategies was to pair the conversation analyst with a designer in a highly interactive collaboration. Our tactics have been effective on our project, leading to valuable results that we believe we could not have obtained using another method. We hope that this paper can serve as a practical guide to those interested in establishing a productive and efficient working relationship between a conversation analyst and the other members of a design team.Comment: 11 page

    Towards a Tool-based Development Methodology for Pervasive Computing Applications

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    Despite much progress, developing a pervasive computing application remains a challenge because of a lack of conceptual frameworks and supporting tools. This challenge involves coping with heterogeneous devices, overcoming the intricacies of distributed systems technologies, working out an architecture for the application, encoding it in a program, writing specific code to test the application, and finally deploying it. This paper presents a design language and a tool suite covering the development life-cycle of a pervasive computing application. The design language allows to define a taxonomy of area-specific building-blocks, abstracting over their heterogeneity. This language also includes a layer to define the architecture of an application, following an architectural pattern commonly used in the pervasive computing domain. Our underlying methodology assigns roles to the stakeholders, providing separation of concerns. Our tool suite includes a compiler that takes design artifacts written in our language as input and generates a programming framework that supports the subsequent development stages, namely implementation, testing, and deployment. Our methodology has been applied on a wide spectrum of areas. Based on these experiments, we assess our approach through three criteria: expressiveness, usability, and productivity
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