Related papers: Towards Semantic Detection of Smells in Cloud Infr…
Smell has a huge influence over how we perceive places. Despite its importance, smell has been crucially overlooked by urban planners and scientists alike, not least because it is difficult to record and analyze at scale. One of the authors…
The adoption of Artificial Intelligence (AI) in high-stakes domains such as healthcare, wildlife preservation, autonomous driving and criminal justice system calls for a data-centric approach to AI. Data scientists spend the majority of…
The popularity of cloud technologies has led to the development of a new type of applications that specifically target cloud environments. Such applications require a lot of cloud infrastructure to run, which brought about the…
Context: Software specifications are usually written in natural language and may suffer from imprecision, ambiguity, and other quality issues, called thereafter, requirement smells. Requirement smells can hinder the development of a project…
Machine learning (ML) codebases face unprecedented challenges in maintaining code quality and sustainability as their complexity grows exponentially. While traditional code smell detection tools exist, they fail to address ML-specific…
Architectural smells such as God Class, Cyclic Dependency, and Hub-like Dependency degrade software quality and maintainability. Existing tools detect such smells but rarely suggest how to fix them. This paper explores the use of…
Much of the existing ML research focuses on model performance metrics, leaving limited attention to the long-term sustainability and resource efficiency of ML applications. While high performance is essential, ensuring efficient resource…
This paper presents a knowledge-based detection of objects approach using the OWL ontology language, the Semantic Web Rule Language, and 3D processing built-ins aiming at combining geometrical analysis of 3D point clouds and specialist's…
Olfactory cues can enhance immersion in interactive media, yet smell remains rare because it is difficult to author and synchronize with dynamic video. Prior olfactory interfaces rely on designer triggers and fixed event-to-odor mappings…
This paper presents a knowledge-based detection of objects approach using the OWL ontology language, the Semantic Web Rule Language, and 3D processing built-ins aiming at combining geometrical analysis of 3D point clouds and specialist's…
Determining the most effective Large Language Model for code smell detection presents a complex challenge. This study introduces a structured methodology and evaluation matrix to tackle this issue, leveraging a curated dataset of code…
Software design debt aims to elucidate the rectification attempts of the present design flaws and studies the influence of those to the cost and time of the software. Design smells are a key cause of incurring design debt. Although the…
The Model Context Protocol (MCP) has rapidly become a de facto standard for connecting LLM-based agents with external tools via reusable MCP servers. In practice, however, server selection and onboarding rely heavily on free-text tool…
Environmental factors determine the smells we perceive, but societal factors factors shape the importance, sentiment and biases we give to them. Descriptions of smells in text, or as we call them `smell experiences', offer a window into…
Requirements form the basis for defining software systems' obligations and tasks. Testable requirements help prevent failures, reduce maintenance costs, and make it easier to perform acceptance tests. However, despite the importance of…
We investigated the capabilities of GPT-4o and Gemini 2.0 Flash for secure Infrastructure as Code (IaC) development. For security smell detection, on the Stack Overflow dataset, which primarily contains small, simplified code snippets, the…
Infrastructure as Code (IaC) enables automated provisioning of large-scale cloud and on-premise environments, reducing the need for repetitive manual setup. However, this automation is a double-edged sword: a single misconfiguration in IaC…
Context: Technical Debt needs to be managed to avoid disastrous consequences, and investigating developers' habits concerning technical debt management is invaluable information in software development. Objective: This study aims to…
Fault-proneness is an indication of programming errors that decreases software quality and maintainability. On the contrary, code smell is a symptom of potential design problems which has impact on fault-proneness. In the literature,…
Foundation models (FM), such as large language models (LLMs), which are large-scale machine learning (ML) models, have demonstrated remarkable adaptability in various downstream software engineering (SE) tasks, such as code completion, code…