Related papers: Do practitioners intentionally self-fix Technical …
Software engineering is a human activity. Despite this, human aspects are under-represented in technical debt research, perhaps because they are challenging to evaluate. This study's objective was to investigate the relationship between…
Self-admitted technical debt (SATD) refers to comments in which developers explicitly acknowledge code issues, workarounds, or suboptimal solutions. SATD is known to significantly increase software maintenance effort. While extensive…
Modern software is developed under considerable time pressure, which implies that developers more often than not have to resort to compromises when it comes to code that is well written and code that just does the job. This has led over the…
Technical debt (TD) is a metaphor for code-related problems that arise as a result of prioritizing speedy delivery over perfect code. Given that the reduction of TDs can have long-term positive impact in the software engineering life-cycle…
Self-Admitted Technical Debt (SATD) is a form of Technical Debt where developers document the debt using source code comments (SATD-C) or issues (SATD-I). However, it is still unclear the circumstances that drive developers to choose one or…
In software development, technical debt (TD) refers to suboptimal implementation choices made by the developers to meet urgent deadlines and limited resources, posing challenges for future maintenance. Self-Admitted Technical Debt (SATD) is…
Research software (also called scientific software) is essential for advancing scientific endeavours. Research software encapsulates complex algorithms and domain-specific knowledge and is a fundamental component of all science. A pervasive…
Technical debt (TD) is a metaphor to describe the trade-off between short-term workarounds and long-term goals in software development. Despite being widely used to explain technical issues in business terms, industry and academia still…
Context. Technical Debt (TD) refers to short-term beneficial software solutions that impede future changes, making TD management essential. However, establishing a TD management (TDM) process is one of the most pressing concerns in…
[Context] Technical debt (TD) in machine learning (ML) systems, much like its counterpart in software engineering (SE), holds the potential to lead to future rework, posing risks to productivity, quality, and team morale. Despite growing…
Technical debt has become a well-known metaphor among software professionals, illustrating how shortcuts taken during development can accumulate and become a burden for software projects. In the traditional notion of technical debt,…
Context: Technical debt (TD) refers to the additional costs incurred due to compromises in software quality, providing short-term advantages during development but potentially compromising long-term quality. Accurate TD forecasting and…
Existing software tools enable characterizing and measuring the amount of technical debt at selective granularity levels. In this paper we aim to study the evolution and characteristics of technical debt in open-source software. We carry…
Self-admitted technical debt (SATD) refers to technical debt that is intentionally introduced by developers and explicitly documented in code comments or other software artifacts (e.g., issue reports) to annotate sub-optimal decisions made…
Context: Technical lag accumulates when software systems fail to keep pace with technological advancements, leading to a deterioration in software quality. Objective: This paper aims to consolidate existing research on technical lag,…
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…
Technical Debt (TD) refers to non-optimal decisions made in software projects that may lead to short-term benefits, but potentially harm the system's maintenance in the long-term. Technical debt management (TDM) refers to a set of…
In software engineering, technical debt, signifying the compromise between short-term expediency and long-term maintainability, is being addressed by researchers through various machine learning approaches. This study seeks to provide a…
Technical debt (TD) refers to suboptimal choices during software development that achieve short-term goals at the expense of long-term quality. Although developers often informally discuss TD, the concept has not yet crystalized into a…
As large language models (LLMs) such as ChatGPT, Copilot, Claude, and Gemini become integrated into software development workflows, developers increasingly leave traces of AI involvement in their code comments. Among these, some comments…