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Social media platforms have become the hubs for various user interactions covering a wide range of needs, including technical support and services related to brands, products, or user accounts. Unfortunately, there has been a recent surge…
Modeling tap or click sequences of users on a mobile device can improve our understandings of interaction behavior and offers opportunities for UI optimization by recommending next element the user might want to click on. We analyzed a…
The advent of increasingly powerful language models has raised expectations for language-based interactions. However, controlling these models is a challenge, emphasizing the need to be able to investigate the feasibility and value of their…
Socio-economic indicators provide context for assessing a country's overall condition. These indicators contain information about education, gender, poverty, employment, and other factors. Therefore, reliable and accurate information is…
Large Language Models (LLMs) offer new avenues to simulate online communities and social media. Potential applications range from testing the design of content recommendation algorithms to estimating the effects of content policies and…
Model-based testing relies on behavior models for the generation of model traces: input and expected output---test cases---for an implementation. We use the case study of an automotive network controller to assess different test suites in…
Meta-World is widely used for evaluating multi-task and meta-reinforcement learning agents, which are challenged to master diverse skills simultaneously. Since its introduction however, there have been numerous undocumented changes which…
Online controlled experiments are a crucial tool to allow for confident decision-making in technology companies. A North Star metric is defined (such as long-term revenue or user retention), and system variants that statistically…
Smart systems for Universities powered by Artificial Intelligence have been massively developed to help humans in various tasks. The chatbot concept is not something new in today society which is developing with recent technology. College…
The proliferation of mobile apps and reduced time in mobile app releases mandates the need for faster and efficient testing of mobile apps, their GUI and functional capabilities. Though, there are wide variety of open source tools and…
Instagram, a social media platform, has in the vicinity of 2 billion active users in 2023. The platform allows users to post photos and videos with one another. However, cyberbullying remains a significant problem for about 50% of young…
PubMed is a freely accessible system for searching the biomedical literature, with approximately 2.5 million users worldwide on an average workday. We have recently developed PubMed Labs (www.pubmed.gov/labs), an experimental platform for…
Although App updates are frequent and software engineers would like to verify updated features only, automated testing techniques verify entire Apps and are thus wasting resources. We present Continuous Adaptation of Learned Models (CALM),…
In the digitized world, smartphones and their apps play an important role. To name just a few examples, some apps offer possibilities for entertainment, others for online banking, and others offer support for two-factor authentication.…
With the growing popularity of Social Web applications, more and more user data is published on the Web everyday. Our research focuses on investigating ways of mining data from such platforms that can be used for modeling users and for…
Online support groups for smoking cessation are economical and accessible, yet they often face challenges with low user engagement and stigma. The use of an automatic conversational agent would improve engagement by ensuring that all user…
Automated model-based test generation presents a viable alternative to the costly manual test creation currently employed for regression testing of web apps. However, existing model inference techniques rely on threshold-based whole-page…
Mobile application marketplaces are responsible for vetting apps to identify and mitigate security risks. Current vetting processes are labor-intensive, relying on manual analysis by security professionals aided by semi-automated tools. To…
We present a comparative docking experiment that aligns human-subject interview data with large language model (LLM)-driven synthetic personas to evaluate fidelity, divergence, and blind spots in AI-enabled simulation. Fifteen early-stage…
This paper presents Mathematical Execution (ME), a new, unified approach for testing numerical code. The key idea is to (1) capture the desired testing objective via a representing function and (2) transform the automated testing problem to…