On the Role of Context in the Design of Mobile Mashups

This paper presents a design methodology and an accompanying platform for the design and fast development of Context-Aware Mobile mashUpS (CAMUS). The approach is characterized by the role given to context as a first-class modeling dimension used to support i) the identification of the most adequate resources that can satisfy the users' situational needs and ii) the consequent tailoring at runtime of the provided data and functions. Context-based abstractions are exploited to generate models specifying how data returned by the selected services have to be merged and visualized by means of integrated views. Thanks to the adoption of Model-Driven Engineering (MDE) techniques, these models drive the flexible execution of the final mobile app on target mobile devices. A prototype of the platform, making use of novel and advanced Web and mobile technologies, is also illustrated

MobiQ: A modular Android application for collecting social interaction, repeated survey, GPS and photographic data

The MobiQ app for Android smartphones is a feature-rich application enabling a novel approach to data collection for longitudinal surveys. It combines continuous automatic background data collection with user supplied data. It can prompt users to complete questionnaires at regular intervals, and allows users to upload photographs for social research projects. The app has the capability to collect GPS location data, and calls and text frequency (excluding content) unobtrusively. The app transmits data to a secure cloud rather than storing research data on the phone, but can also store data temporarily if a data connection is unavailable; hence, MobiQ offers data security advantages over text- or web-based surveys using phones. MobiQ has been pilot tested in the field in a social science research project and is able to collect longitudinal social research data. Due to its modular and flexible design, MobiQ can easily be adapted to suit different research questions. Furthermore, its core design approach which allows for long-term power efficient data collection can be re-used outside the social sciences domain for other kinds of smartphone-based data-driven projects. Projects that have a requirement for communications-based, sensors-based, user-based data collection or any combination of these may find our code and design approach beneficial. For example, MobiQ code and architecture has been successfully adapted to build an app for a project investigating smartphone-based implicit authentication for mobile access control

Interaction mining mobile apps

Millions of mobile apps are used by billions of users every day. Although the design of these apps play an important role in their adoption, the design process still remains complex and time intensive. At the same time, existing apps embody multiple solutions to numerous design problems faced by app developers. How do we make this design knowledge embedded in existing apps accessible to designers? And how can it help simplify the app design process? This dissertation introduces interaction mining, a technique to capture the designs of mobile apps in a way that supports data-driven design applications. It presents systems that implement interaction mining for Android apps without requiring any access to their source code making it possible to design mine apps at an unprecedented scale. It presents Rico, the largest publicly available mobile app design repository to date. It discusses how such repositories created using interaction mining can be used to train models that enable applications such as keyword and example-based search interactions for mobile screens and user flows. It also presents zero-integration performance testing (ZIPT), a novel technique for testing app designs. It demonstrates how ZIPT can be used to help designers understand which examples to draw from in the early stages of the app design process and perform comparative testing at scale with low cost and effort in the later stages of the process

Data Driven Analysis of Tiny Touchscreen Performance with MicroJam

The widespread adoption of mobile devices, such as smartphones and tablets, has made touchscreens a common interface for musical performance. New mobile musical instruments have been designed that embrace collaborative creation and that explore the affordances of mobile devices, as well as their constraints. While these have been investigated from design and user experience perspectives, there is little examination of the performers' musical outputs. In this work, we introduce a constrained touchscreen performance app, MicroJam, designed to enable collaboration between performers, and engage in a novel data-driven analysis of more than 1600 performances using the app. MicroJam constrains performances to five seconds, and emphasises frequent and casual music making through a social media-inspired interface. Performers collaborate by replying to performances, adding new musical layers that are played back at the same time. Our analysis shows that users tend to focus on the centre and diagonals of the touchscreen area, and tend to swirl or swipe rather than tap. We also observe that while long swipes dominate the visual appearance of performances, the majority of interactions are short with limited expressive possibilities. Our findings are summarised into a set of design recommendations for MicroJam and other touchscreen apps for social musical interaction

Targeting parents for childhood weight management: development of a theory-driven and user-centered healthy eating app

Background: The proliferation of health promotion apps along with mobile phones' array of features supporting health behavior change offers a new and innovative approach to childhood weight management. However, despite the critical role parents play in children's weight related behaviors, few industry-led apps aimed at childhood weight management target parents. Furthermore, industry-led apps have been shown to lack a basis in behavior change theory and evidence. Equally important remains the issue of how to maximize users' engagement with mobile health (mHealth) interventions where there is growing consensus that inputs from the commercial app industry and the target population should be an integral part of the development process. Objective: The aim of this study is to systematically design and develop a theory and evidence-driven, user-centered healthy eating app targeting parents for childhood weight management, and clearly document this for the research and app development community. Methods: The Behavior Change Wheel (BCW) framework, a theoretically-based approach for intervention development, along with a user-centered design (UCD) philosophy and collaboration with the commercial app industry, guided the development process. Current evidence, along with a series of 9 focus groups (total of 46 participants) comprised of family weight management case workers, parents with overweight and healthy weight children aged 5-11 years, and consultation with experts, provided data to inform the app development. Thematic analysis of focus groups helped to extract information related to relevant theoretical, user-centered, and technological components to underpin the design and development of the app. Results: Inputs from parents and experts working in the area of childhood weight management helped to identify the main target behavior: to help parents provide appropriate food portion sizes for their children. To achieve this target behavior, the behavioral diagnosis revealed the need for eliciting change in parents' capability, motivation, and opportunity in 10-associated Theoretical Domains Framework (TDF) domains. Of the 9 possible intervention functions, 6 were selected to bring about this change which guided the selection of 21 behavior change techniques. Parents' preferences for healthy eating app features revolved around four main themes (app features, time saving and convenience, aesthetics, and gamification) whereupon a criterion was applied to guide the selection on which preferences should be integrated into the design of the app. Collaboration with the app company helped to build on users' preferences for elements of gamification such as points, quizzes, and levels to optimize user engagement. Feedback from parents on interactive mock-ups helped to inform the final development of the prototype app. Conclusions: Here, we fully explicate a systematic approach applied in the development of a family-oriented, healthy eating health promotion app grounded in theory and evidence, and balanced with users' preferences to help maximize its engagement with the target population

Domain-Specific Modeling and Code Generation for Cross-Platform Multi-Device Mobile Apps

Nowadays, mobile devices constitute the most common computing device. This new computing model has brought intense competition among hardware and software providers who are continuously introducing increasingly powerful mobile devices and innovative OSs into the market. In consequence, cross-platform and multi-device development has become a priority for software companies that want to reach the widest possible audience. However, developing an application for several platforms implies high costs and technical complexity. Currently, there are several frameworks that allow cross-platform application development. However, these approaches still require manual programming. My research proposes to face the challenge of the mobile revolution by exploiting abstraction, modeling and code generation, in the spirit of the modern paradigm of Model Driven Engineering

Overcoming Language Dichotomies: Toward Effective Program Comprehension for Mobile App Development

Mobile devices and platforms have become an established target for modern software developers due to performant hardware and a large and growing user base numbering in the billions. Despite their popularity, the software development process for mobile apps comes with a set of unique, domain-specific challenges rooted in program comprehension. Many of these challenges stem from developer difficulties in reasoning about different representations of a program, a phenomenon we define as a "language dichotomy". In this paper, we reflect upon the various language dichotomies that contribute to open problems in program comprehension and development for mobile apps. Furthermore, to help guide the research community towards effective solutions for these problems, we provide a roadmap of directions for future work.Comment: Invited Keynote Paper for the 26th IEEE/ACM International Conference on Program Comprehension (ICPC'18