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The metaphor of Technical Debt (TD) has generated a conceptual framework on factors that weaken the quality of software and accumulate a repair cost. However, user-related aspects like user experience (UX) receive little consideration among TD types, for reasons like the substantial focus on code TD, some dynamics inherent to agile processes, and an apparent lack of cumulative cost over time. This article has two main goals: first, to present evidence of the existence of UXDebt as a type of TD, with a cumulative cost for the development team as well as stakeholders; second, to propose a definition and characterization of UXDebt that may serve as a frame for further research on methods and tools for continuous management within agile processes. For the first goal, we have compiled evidence on the current state of UXDebt from three sources: a literature review, a survey among software engineering professionals in agile teams, and the analysis of UX issues in GitHub. All sources have evidenced some form of UXDebt; surveyed practitioners have recognized its poor management with a cost for the entire team that accumulates over time. Moreover, issue-tracking systems allow to visualize and measure a technical form of UXDebt. For the second goal, we have defined a conceptual model that characterizes UXDebt in terms of both technical and non-technical aspects. On the technical side, we propose the notion of UX smells which allows us to discuss concrete management activities.

This study surveys the state of the art in usability and user experience strategies applied to applications that deal with large amounts of data in the field of Cultural Heritage, highlighting the most prominent aspects and underlining the under-explored. In these applications, large amounts of data need to be wisely presented to help final users at drawing conclusions and making decisions. While sophisticated technology may be used to improve the user experience, it should not be applied to the detriment of usability, which is critical for the success of these applications. We performed a systematic mapping study to classify the literature retrieved in the four largest scientific databases by a structured search string. We classify applications according to purpose, intended users, the way they address and evaluate UX and usability, among others, and include the analysis of combined results through maps.Findings reveal the contradiction that while most articles are intended for the education and tourism of the general public, only half of the studies evaluate usability. Moreover, there is a significant research gap in user interfaces for systems in the context of preventive conservation, for research, assessment and decision assistance.This is the first systematic mapping study combining usability and Cultural Heritage, especially for data-oriented applications. It shows that more research is necessary to assist conservators and researchers, and to address usability from early stages of development., Laboratorio de Arquitectura y Hábitat Sustentable, Laboratorio de Investigación y Formación en Informática Avanzada

The product of good design should render a tool invisible for a user who is executing a task. Unfortunately, web applications are often far from invisible to users, who struggle with poor design of websites and processes in them. We are particularly interested in web processes that involve form filling, so we have been studying how people interact with web forms. Besides cataloguing user interaction problems that are common in web forms, we have noticed that, in many cases, there is a single form element or widget to blame for a certain interaction problem, because such widget is not the most appropriate one for the required input in that particular context. This unfitness of the widget causes an extra burden to the user, which we call interaction effort. In this work we propose measuring the interaction effort of a widget with a unified score based on micro-measures automatically captured from interaction logs. We present the micromeasures that were found relevant to predict the interaction effort in 6 different types of web forms widgets. We describe a large data collection process and prediction models, showing that it is indeed possible to automatically predict a widget interaction effort score by learning from expert human ratings. We consequently believe that the interaction effort could be used as an effective metric to compare small variations in a design in terms of user experience.

Online customers frequently conduct activities that involve multi-criteria decision-making. They analyze and compare alternatives considering a set of shared characteristics. Websites present the information of products without special support for these activities. Moreover, the products of interest for the customer are frequently scattered across various shops, with no support to collect and compare them in a consistent and customized manner. We argue that multi-criteria decision-making methods (such as Analytic Hierarchy Process) can be effectively offered to online customers. In this article, we present an approach and supporting tools to enable multi-criteria decision-making on any website and across websites. They are based on web-augmentation to extract information items from websites, and the Analytic Hierarchy Process (AHP) to model multi-criteria decisions. The approach and tools were experimentally evaluated with end-users in two different countries. An illustrative scenario provides insight into the application of the approach and the role of the supporting tools. Evaluation showed that users appreciate creating AHP models specific to their needs, and trust the decisions they make using these models. Participants were reluctant to trust reusable decision profiles (i.e., AHP models created by other users). The numerous pairwise comparisons required by AHP in the presence of multiple criteria and alternatives, was reported as a drawback. However, participants indicated that the proposed smart-ranking functionality represented a good mechanism to cope with it., Laboratorio de Investigación y Formación en Informática Avanzada

Usability and user interaction improvement is a central task in web development to guarantee the success of a web application. However, designers are barely able to keep up with the current development cycle because their practices are too costly, while interaction issues accumulate in applications that end-users keep suffering. In this work, we propose a method for designers to rapidly explore solutions through visual programming to the interaction problems of an application under development, even when it has been already deployed. The method is realized by a tool called UX-Painter, an exploratory tool for designers to apply quick fixes to interaction issues at the client-side of a web application without the need of any script programming knowledge. The palette of available fixes in UX-Painter are client-side web refactorings, i.e., changes to web page elements that solve specific user interaction problems without changing the underlying functionality. UX-Painter allows designers to quickly set up new versions of a web application by combining refactorings to create alternative designs for user testing or an inspection review. UX-Painter also provides the means to communicate design improvements, as a sequence of refactorings with clear semantics. We show the feedback provided by interviews with designers about UX-Painter's functionality and the results of a user test about its usability.

The goal of this research is to develop an A/B testing method to automatically compare the user experience (UX) of alternative designs for a web application in a real context with a large number of users. The challenge that it poses is to find mechanisms to predict the UX with machine learning techniques. This submission outlines the motivation, research goal, current status and remaining work.

Automating usability diagnosis and repair can be a powerful assistance to usability experts and even less knowledgeable developers. To accomplish this goal, evaluating user interaction automatically is crucial, and it has been broadly explored. However, most works focus in long interaction sessions, which makes it difficult to tell how individual interface components influence usability. In contrast, this work aims to compare how different widgets perform for a same task, in the context of evaluating alternative designs for small components, implemented as refactorings. For this purpose, we propose a unified score to compare the widgets involved in each refactoring by the level of effort required by users to interact with them. This score is based on micro-measures automatically captured from interaction logs, so it can be automatically predicted. We show the results of predicting such score using decision trees.

Client-Side Web Refactorings (CSWRs) allow improving interaction aspects of web applications by applying changes to the user interface without altering the code base, even in production settings. However, developers are not always willing, or even allowed to apply external adaptations to their applications’ user interface. Besides, CSWRs do not guarantee improvements in all contexts, so it may be unwise to install them in a production version. We propose a tool that allows creating private versions of a running web application almost automatically. Using this tool, developers or usability experts can easily combine CSWRs to create alternative versions of web applications, without the need of creating a cloned sandbox environment for each version. This yields many uses, such as quickly setting up user tests, showing live alternatives to Product Owners, and even performing A/B testing. The tool is built on top of Kobold, a service that allows applying CSWRs to fix usability smells. Kobold with versioning is available at: https://autorefactoring.lifia.info.unlp.edu.ar. A screencast of the tool is available at https://youtu.be/LVc3BOtVP3I.