4 research outputs found

    A Focus+Context Approach to Alleviate Cognitive Challenges of Editing and Debugging UML Models

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    Copyright (c) 2019 IEEE Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Model-Driven Engineering has been proposed to increase the productivity of developing a software system. Despite its benefits, it has not been fully adopted in the software industry. Research has shown that modelling tools are amongst the top barriers for the adoption of MDE by industry. Recently, researchers have conducted empirical studies to identify the most severe cognitive difficulties of modellers when using UML model editors. Their analyses show that users’ prominent challenges are in remembering the contextual information when performing a particular modelling task; and locating, understanding, and fixing errors in the models. To alleviate these difficulties, we propose two Focus+Context user interfaces that provide enhanced cognitive support and automation in the user’s interaction with a model editor. Moreover, we conducted two empirical studies to assess the effectiveness of our interfaces on human users. Our results reveal that our interfaces help users 1) improve their ability to successfully fulfil their tasks, 2) avoid unnecessary switches among diagrams, 3) produce more error-free models, 4) remember contextual information, and 5) reduce time on tasks.NSERC CREATE 465463-2015 NSERC Discovery Grant 15524

    Chatbots for Modelling, Modelling of Chatbots

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    Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingeniería Informática. Fecha de Lectura: 28-03-202

    Flexible photo retrieval (FlexPhoReS) : a prototype for multimodel personal digital photo retrieval

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    Digital photo technology is developing rapidly and is motivating more people to have large personal collections of digital photos. However, effective and fast retrieval of digital photos is not always easy, especially when the collections grow into thousands. World Wide Web (WWW) is one of the platforms that allows digital photo users to publish a collection of photos in a centralised and organised way. Users typically find their photos by searching or browsing uSing a keyboard and mouse. Also in development at the moment are alternative user interfaces such as graphical user interfaces with speech (S/GUI) and other multimodal user interfaces which offer more flexibility to users. The aim of this research was to design and evaluate a flexible user interface for a web based personal digital photo retrieval system. A model of a flexible photo retrieval system (FlexPhoReS) was developed based on a review of the literature and a small-scale user study. A prototype, based on the model, was built using MATLAB and WWW technology. FlexPhoReS is a web based personal digital photo retrieval prototype that enables digital photo users to . accomplish photo retrieval tasks (browsing, keyword and visual example searching (CBI)) using either mouse and keyboard input modalities or mouse and speech input modalities. An evaluation with 20 digital photo users was conducted using usability testing methods. The result showed that there was a significant difference in search performance between using mouse and keyboard input modalities and using mouse and speech input modalities. On average, the reduction in search performance time due to using mouse and speech input modalities was 37.31%. Participants were also significantly more satisfied with mouse and speech input modalities than with mouse and keyboard input modalities although they felt that both were complementary. This research demonstrated that the prototype was successful in providing a flexible model of the photo retrieval process by offering alternative input modalities through a multimodal user interface in the World Wide Web environment.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    A User-Centric Approach to Improve the Quality of UML-like Modelling Tools and Reduce the Efforts of Modelling

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    As software systems grow in size and complexity, their development and maintenance are becoming increasingly challenging. Model-Driven Engineering (MDE) has been proposed as a means to increase the developer's productivity of such large-scale complex software systems. Despite its benefits, MDE has not been fully adopted in the software industry due to several barriers. Research has shown that modelling tools are amongst the top barriers for the industry's reluctance to adopt MDE, mostly because there is a little investigation of the modellers' interactions with modelling tools when editing and debugging models, which are cognitively difficult tasks. More specifically, MDE tool research has not considered 1) a thorough analysis of modellers and their tasks, to understand their challenges of using modelling tools, 2) the underlying human-cognitive factors, and 3) a systematic assessment of the effectiveness of proposed solutions (i.e., tooling techniques) on human users. This thesis argues that MDE tools can be enhanced to overcome (some of) the challenges of adoption by considering human-cognitive factors (i.e., user-centric) when designing and proposing model-easing techniques for model editors. We advance our thesis in three main steps. As a first step, we conducted an empirical study to identify the most-severe cognitive difficulties of modellers when using UML model editors. In our study, we asked the recruited subjects to perform several model-editing and model-debugging tasks. We collected information during the sessions that could help us understand the subjects' cognitive challenges. The results show that users face multiple challenges, amongst which the most prominent challenges are remembering contextual information when performing a particular modelling task; and locating, understanding, and fixing errors in the models. In the second step, we identified the cognitive factors that drive the most prominent challenges and subsequently devised several tooling advancements that provide enhanced cognitive support and automation in the users' interaction with a model editor. The philosophy behind our tooling advancements is to provide the contextual information that are relevant to performing a particular modelling task, thereby, alleviating the modellers' cognitive challenges of recollecting information from different diagrams. We also proposed an on-the-fly error-resolution technique that aims at resolving errors as they occur. We implemented our Eclipse-based model-editor and embedded our tooling techniques in the tool. Lastly, we conducted two empirical studies to assess the effectiveness of our model-editor on human users. The Context study aimed at evaluating our tool's ability to reduce the challenges of remembering contextual information, whereas the Debugging study aimed at assessing our tool's ability to improve the users' experience of debugging models. Our results reveal that our interfaces help users 1) improve their ability to successfully fulfil their tasks, 2) avoid unnecessary context switches among diagrams, 3) produce more error-free models, 4) remember contextual information, and 5) reduce time on tasks
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