相关论文: Identifying Technical Debt and Its Types Across Di…

Keeping track of and managing Self-Admitted Technical Debts (SATDs) are important to maintaining a healthy software project. This requires much time and effort from human experts to identify the SATDs manually. The current automated…

Background: The "Technical Debt Dataset" (TDD) is a comprehensive dataset on technical debt (TD) in the main branches of more than 30 Java projects. However, some TD items produced by SonarQube are not included for many commits, for…

Self-admitted technical debt refers to situations where a software developer knows that their current implementation is not optimal and indicates this using a source code comment. In this work, we hypothesize that it is possible to develop…

Self-Admitted Technical Debt (SATD) refers to instances where developers knowingly introduce suboptimal solutions into code and document them, often through textual artifacts. This paper provides a comprehensive state-of-practice report on…

In today's digital landscape, the importance of timely and accurate vulnerability detection has significantly increased. This paper presents a novel approach that leverages transformer-based models and machine learning techniques to…

Context: Technical Debt is a metaphor used to describe code that is "not quite right." Although TD studies have gained momentum, TD has yet to be studied as thoroughly in non-Object-Oriented (OO) or scientific software such as R. R is a…

Software documentation often struggles to catch up with the pace of software evolution. The lack of correct, complete, and up-to-date documentation results in an increasing number of documentation defects which could introduce delays in…

Technical Debt analysis is increasing in popularity as nowadays researchers and industry are adopting various tools for static code analysis to evaluate the quality of their code. Despite this, empirical studies on software projects are…

Background: Software security is crucial to ensure that the users are protected from undesirable consequences such as malware attacks which can result in loss of data and, subsequently, financial loss. Technical Debt (TD) is a metaphor…

Multi-task learning is a paradigm that leverages information from related tasks to improve the performance of machine learning. Self-Admitted Technical Debt (SATD) are comments in the code that indicate not-quite-right code introduced for…

Nondestructive testing (NDT) is widely applied to defect identification of turbine components during manufacturing and operation. Operational efficiency is key for gas turbine OEM (Original Equipment Manufacturers). Automating the…

NonTechnical Debt (NTD) is a common challenge in agile software development, manifesting in four critical forms, Process Debt, Social Debt, People Debt, Organizational debt. NODLA project is a collaboration between Karlstad University and…

The adoption of Machine and Deep Learning (ML/DL) technologies introduces maintenance challenges, leading to Technical Debt (TD). Algorithm Debt (AD) is a TD type that impacts the performance and scalability of ML/DL systems. A review of 42…

Technical debt is a metaphor that describes the long term effects of shortcuts taken in software development activities to achieve near term goals. In this study, we explore a new context of technical debt that relates to database…

Technical debt refers to taking shortcuts to achieve short-term goals, which might negatively influence software maintenance in the long-term. There is increasing attention on technical debt that is admitted by developers in source code…

Software practitioners can make sub-optimal decisions concerning requirements during gathering, documenting, prioritizing, and implementing requirements as software features or architectural design decisions -- this is captured by the…

Context. Companies commonly invest effort to remove technical issues believed to impact software qualities, such as removing anti-patterns or coding styles violations. Objective. Our aim is to analyze the diffuseness of Technical Debt (TD)…

Context: Software vulnerabilities pose significant security threats to software systems, especially as software is increasingly used across many areas of daily life, including health, government, and finance. Recently, transformer-based…

Motivation: Technical debt is a metaphor that describes not-quite-right code introduced for short-term needs. Developers are aware of it and admit it in source code comments, which is called Self- Admitted Technical Debt (SATD). Therefore,…

Effective prioritization of issue reports is crucial in software engineering to optimize resource allocation and address critical problems promptly. However, the manual classification of issue reports for prioritization is laborious and…