VLDB 2026 Research / reviewers in the wild / expert
Shavindra Wickramathilaka
dblp:346/0779
· DBLP profile ↗
3ranked-venue papers
2as first author
3since 2021 · last 2025
0000-0002-4732-2264ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 2 first-author · 2 since 2021Human-computer interaction and ubiquitous computing · 2 · 1 first-author · 2 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Adaptive and accessible user interfaces for seniors through model-driven engineeringabstractAbstract The use of diverse mobile applications among senior users is becoming increasingly widespread. However, many of these apps contain accessibility problems that result in negative user experiences for seniors. A key reason is that software practitioners often lack the time or resources to address the broad spectrum of age-related accessibility and personalisation needs. As current developer tools and practices encourage one-size-fits-all interfaces with limited potential to address the diversity of senior needs, there is a growing demand for approaches that support the systematic creation of adaptive, accessible app experiences. To this end, we present AdaptForge , a novel model-driven engineering (MDE) approach that enables advanced design-time adaptations of mobile application interfaces and behaviours tailored to the accessibility needs of senior users. AdaptForge uses two domain-specific languages (DSLs) to address age-related accessibility needs. The first model defines users’ context-of-use parameters, while the second defines conditional accessibility scenarios and corresponding UI adaptation rules. These rules are interpreted by an MDE workflow to transform an app’s original source code into personalised instances. We also report evaluations with professional software developers and senior end-users, demonstrating the feasibility and practical utility of AdaptForge . Shavindra Wickramathilaka, John C. Grundy, Kashumi Madampe, Omar Haggag |
Autom. Softw. Eng. | 1 |
| 2024 | Development of an Adaptive User Support System Based on Multimodal Large Language ModelsabstractAs software systems become more complex, some users find it challenging to use these tools efficiently, leading to frustration and decreased productivity. We tackle the shortcomings of conventional user support mechanisms in software and aim to create and assess a user support system that integrates Multimodal Large Language Models (MLLMs) for producing support messages. Our system initially segments the user interface to serve as a reference for selection and requests users to specify their preferences for support messages. Following this, the system creates personalised user support messages for each individual. We propose that user support systems enhanced with MLLMs can provide more efficient and bespoke assistance compared to conventional methods. Wei Wang 0376, Lin Li 0066, Shavindra Wickramathilaka, John C. Grundy, Hourieh Khalajzadeh, Humphrey O. Obie, Anuradha Madugalla |
VL/HCC | 3 |
| 2023 | Addressing Age-Related Accessibility Needs of Senior Users Through Model-Driven EngineeringabstractOne of the main reasons that cause seniors to face accessibility barriers when trying to use software applications is that the age-related user interface (UI) needs of seniors (e.g., physical and cognitive limitations) are not properly addressed in software user interfaces. The existing literature proposes model-driven engineering based UI adaptations as a prominent solution for this phenomenon. But in our exploration into the domain, we identified that the existing work lacks comprehensiveness when it comes to integrating accessibility into software modelling tools and methods when compared to a well-recognised accessibility standard such as the Web Content Accessibility Guidelines (WCAG). Thus in this paper, we outline a research roadmap that aims to use WCAG as a reference framework to design domain-specific languages that model the diverse accessibility scenarios of senior users via user context information and UI adaptation rules modelling so that they meet the accessibility standards specified in WCAG. Shavindra Wickramathilaka, Ingo Mueller 0001 |
CHASE | 1 |