Related papers: User Story Tutor (UST) to Support Agile Software D…
Multi-modal models have shown appealing performance in visual recognition tasks, as free-form text-guided training evokes the ability to understand fine-grained visual content. However, current models cannot be trivially applied to scene…
Agile teams juggle multiple tasks so professionals are often assigned to multiple projects, especially in service organizations that monitor and maintain a large suite of software for a large user base. If we could predict changes in…
It is known that user-centered approaches to requirements engineering in general lead to a better suited product for the end-users. LLM4RE provides promising approaches to support the requirements elicitation process (e.g. classification of…
Although agile software development methods have caught the attention of software engineers and researchers worldwide, scientific research still remains quite scarce. The aim of this study is to order and make sense of the different agile…
In recent years, mobile accessibility has become an important trend with the goal of allowing all users the possibility of using any app without many limitations. User reviews include insights that are useful for app evolution. However,…
User stories are essential in agile development, yet often missing or outdated in legacy and poorly documented systems. We investigate whether large language models (LLMs) can automatically recover user stories directly from source code and…
The increasing demand for programmers has led to a surge in participants in programming courses, making it increasingly challenging for instructors to assess student code manually. As a result, automated programming assessment systems…
Modern Software Engineering era is moving fast with the assistance of artificial intelligence (AI), especially Large Language Models (LLM). Researchers have already started automating many parts of the software development workflow.…
With the servitization of business, understanding how users experience services becomes a crucial success factor for companies. Therefore, there is a need to include feedback from user experiences in the software engineering process.…
Place recognition is key to Simultaneous Localization and Mapping (SLAM) and spatial perception. However, a place recognition in the wild often suffers from erroneous predictions due to image variations, e.g., changing viewpoints and street…
We consider the problem of assessing the changing performance levels of individual students as they go through online courses. This student performance (SP) modeling problem is a critical step for building adaptive online teaching systems.…
Context: The active involvement of users and customers in agile software development remains a persistent challenge in practice. For this reason, it is important that students in higher education become familiar with good practices in Agile…
Aspect Sentiment Triplet Extraction (ASTE) is a burgeoning subtask of fine-grained sentiment analysis, aiming to extract structured sentiment triplets from unstructured textual data. Existing approaches to ASTE often complicate the task…
With the increasing emphasis on how mobile technologies are experienced in everyday life, researchers are increasingly emphasizing the use of in-situ methods such as Experience Sampling and Day Reconstruction. In our line of research we…
Mobile applications (apps) are often developed by only a small number of developers with limited resources, especially in the early years of the app's development. In this setting, many requirements acquisition activities, such as…
A main challenge faced by non-profit organisations providing computer science education to under-represented groups are the high drop-out rates. This issue arises from various factors affecting both students and teachers, such as the…
Evaluation is crucial in the development process of task-oriented dialogue systems. As an evaluation method, user simulation allows us to tackle issues such as scalability and cost-efficiency, making it a viable choice for large-scale…
AI-assisted tools support developers in performing cognitively demanding tasks such as bug detection and code readability assessment. Despite the advancements in the technical characteristics of these tools, little is known about how…
Context: It is an enigma that agile projects can succeed 'without requirements' when weak requirements engineering is a known cause for project failures. While agile development projects often manage well without extensive requirements test…
Clinical decision support tools (DST) promise improved healthcare outcomes by offering data-driven insights. While effective in lab settings, almost all DSTs have failed in practice. Empirical research diagnosed poor contextual fit as the…