相关论文: Towards a Technical Debt for Recommender System

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…

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,…

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…

Technical debt is a metaphor indicating sub-optimal solutions implemented for short-term benefits by sacrificing the long-term maintainability and evolvability of software. A special type of technical debt is explicitly admitted by software…

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…

The recent advancements in machine learning (ML) have demonstrated the potential for providing a powerful solution to build complex prediction systems in a short time. However, in highly regulated industries, such as the financial…

Technical debt (TD) is a metaphor that is used to communicate the consequences of poor software development practices to non-technical stakeholders. In recent years, it has gained significant attention in agile software development (ASD).…

To meet project timelines or budget constraints, developers intentionally deviate from writing optimal code to feasible code in what is known as incurring Technical Debt (TD). Furthermore, as part of planning their correction, developers…

Applications and systems are constantly faced with decisions that require picking from a set of actions based on contextual information. Reinforcement-based learning algorithms such as contextual bandits can be very effective in these…

Technical debt refers to the consequences of sub-optimal decisions made during software development that prioritize short-term benefits over long-term maintainability. Self-Admitted Technical Debt (SATD) is a specific form of technical…

Recommender systems support decisions in various domains ranging from simple items such as books and movies to more complex items such as financial services, telecommunication equipment, and software systems. In this context,…

This work examines the role of recommender systems in promoting sustainability, social responsibility, and accountability, with a focus on alignment with the United Nations Sustainable Development Goals (SDGs). As recommender systems become…

Background: Software companies must balance fast value delivery with quality, a trade-off that can introduce technical debt and potentially waste developers' time. As software systems evolve, technical debt tends to increase. However,…

Human behavioral patterns and consumption paradigms have emerged as pivotal determinants in environmental degradation and climate change, with quotidian decisions pertaining to transportation, energy utilization, and resource consumption…

Recommender systems can be characterized as software solutions that provide users convenient access to relevant content. Traditionally, recommender systems research predominantly focuses on developing machine learning algorithms that aim to…

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…

Background: Technical Debt (TD) describes suboptimal software development practices with long-term consequences, such as defects and vulnerabilities. Deadlines are a leading cause of the emergence of TD in software systems. While multiple…

Context: There is an increase in the investment and development of data-intensive (DI) solutions, systems that manage large amounts of data. Without careful management, this growing investment will also grow associated technical debt (TD).…

Technical debt---design shortcuts taken to optimize for delivery speed---is a critical part of long-term software costs. Consequently, automatically detecting technical debt is a high priority for software practitioners. Software quality…

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…