Related papers: Locating Community Smells in Software Development …
Network analysis is increasingly important across various fields, including the fragrance industry, where perfumes are represented as nodes and shared user preferences as edges in perfume networks. Community detection can uncover clusters…
This study explores the intricate relationship between sentiment analysis (SA) and code quality within machine learning (ML) projects, illustrating how the emotional dynamics of developers affect the technical and functional attributes of…
Software development is a collaborative task. Previous research has shown social aspects within development teams to be highly relevant for the success of software projects. A team's mood has been proven to be particularly important. It is…
The Large Language Models (LLMs) have demonstrated great potential in code-related tasks. However, most research focuses on improving the output quality of LLMs (e.g., correctness), and less attention has been paid to the LLM input (e.g.,…
The paper investigates the problem of finding communities in complex network systems, the detection of which allows a better understanding of the laws of their functioning. To solve this problem, two approaches are proposed based on the use…
Nowadays, modern applications are developed using components written in different programming languages. These systems introduce several advantages. However, as the number of languages increases, so does the challenges related to the…
Detecting community structure in social networks is a fundamental problem empowering us to identify groups of actors with similar interests. There have been extensive works focusing on finding communities in static networks, however, in…
Communities are fundamental entities for the characterization of the structure of real networks. The standard approach to the identification of communities in networks is based on the optimization of a quality function known as…
Spreadsheets are commonly used in organizations as a programming tool for business-related calculations and decision making. Since faults in spreadsheets can have severe business impacts, a number of approaches from general software…
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…
Nowadays, we are witnessing an increasing adoption of Deep Learning (DL) based software systems in many industries. Designing a DL program requires constructing a deep neural network (DNN) and then training it on a dataset. This process…
Automated deployment and management of Cloud applications relies on descriptions of their deployment topologies, often referred to as Infrastructure Code. As the complexity of applications and their deployment models increases, developers…
Community detection is a very active field in complex networks analysis, consisting in identifying groups of nodes more densely interconnected relatively to the rest of the network. The existing algorithms are usually tested and compared on…
Many real world systems or web services can be represented as a network such as social networks and transportation networks. In the past decade, many algorithms have been developed to detect the communities in a network using connections…
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…
Unit testing is an essential component of the software development life-cycle. A developer could easily and quickly catch and fix software faults introduced in the source code by creating and running unit tests. Despite their importance,…
Context: Code smells (CS) tend to compromise software quality and also demand more effort by developers to maintain and evolve the application throughout its life-cycle. They have long been catalogued with corresponding mitigating solutions…
CONTEXT: There has been a rapid growth in the use of data analytics to underpin evidence-based software engineering. However the combination of complex techniques, diverse reporting standards and poorly understood underlying phenomena are…
Machine Learning (ML) projects incur novel challenges in their development and productionisation over traditional software applications, though established principles and best practices in ensuring the project's software quality still…
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…