相关论文: Architectural Archipelagos: Technical Debt in Long…

As Large Language Models (LLMs) transition from code completion tools to autonomous system architects, their impact on long-term software maintainability remains unquantified. While existing research benchmarks functional correctness…

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…

Context: Contemporary software development is typically conducted in dynamic, resource-scarce environments that are prone to the accumulation of technical debt. While this general phenomenon is acknowledged, what remains unknown is how…

Architectural debt is a form of technical debt that derives from the gap between the architectural design of the system as it "should be" compared to "as it is". We measured architecture debt in two ways: 1) in terms of system-wide coupling…

Advances in AI have led to new types of technical debt in software engineering projects. AI-based competition platforms face challenges due to rapid prototyping and a lack of adherence to software engineering principles by participants,…

Architectural technical debt (ATD) represents trade-offs in software architecture that accelerate initial development but create long-term maintenance challenges. ATD, in particular when self-admitted, impacts the foundational structure of…

Generative AI is accelerating software development, but may quietly shift where the most significant risks lie. As AI generates code faster than teams can understand it, two under appreciated forms of debt accumulate: cognitive debt, the…

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…

Fixing bugs is an important phase in software development and maintenance. In practice, the process of bug fixing may conflict with the release schedule. Such confliction leads to a trade-off between software quality and release schedule,…

To complete tasks faster, developers often have to sacrifice the quality of the software. Such compromised practice results in the increasing burden to developers in future development. The metaphor, technical debt, describes such practice.…

The integration of Large Language Models (LLMs) into the software development lifecycle (SDLC) masks a critical socio-technical failure: Cognitive-Systemic Collapse. This paper introduces "Epistemological Debt," the hidden carrying cost…

In the software development industry, technical debt is regarded as a critical issue in term of the negative consequences such as increased software development cost, low product quality, decreased maintainability, and slowed progress to…

Context: Software start-ups are young companies aiming to build and market software-intensive products fast with little resources. Aiming to accelerate time-to-market, start-ups often opt for ad-hoc engineering practices, make shortcuts in…

Background: With the rising popularity of Artificial Intelligence (AI), there is a growing need to build large and complex AI-based systems in a cost-effective and manageable way. Like with traditional software, Technical Debt (TD) will…

Context: Self-admitted technical debt (SATD) occurs when developers acknowledge shortcuts in code. In scientific software (SSW), such debt poses unique risks to the validity and reproducibility of results. Objective: This study aims to…

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,…

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…

Technical debt is a metaphor used to convey the idea that doing things in a "quick and dirty" way when designing and constructing a software leads to a situation where one incurs more and more deferred future expenses. Similarly to…

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), referring to comments flagged by developers that explicitly acknowledge suboptimal code or incomplete functionality, has received extensive attention in machine learning (ML) and traditional (Non-ML)…