Related papers: Quantifying Technical Debt: A Systematic Mapping S…
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…
There is a lack of quantitative measures to evaluate the progression of topics through time in dynamic topic models (DTMs). Filling this gap, we propose a novel evaluation measure for DTMs that analyzes the changes in the quality of each…
In this paper, we present the Tokenized Sovereign Debt Conversion Mechanism (TSDCM), a smart-contracted instrument that, upon meeting both debt-to-GDP and GDP-growth thresholds, automates the retirement of sovereign debt. TSDCM initiates…
Software and systems traceability is essential for downstream tasks such as data-driven software analysis and intelligent tool development. However, despite the increasing attention to mining and understanding technical debt in software…
The durability and quality of software contributions are critical factors in the long-term maintainability of a codebase. This paper introduces the Time to Modification (TTM) Theory, a novel approach for quantifying code quality by…
Context: Technical Debt (TD) can be paid back either by those that incurred it or by others. We call the former self-fixed TD, and it can be particularly effective, as developers are experts in their own code and are well-suited to fix the…
The impact of Technical Debt (TD) on software maintenance and evolution is of great concern, but recent evidence shows that a considerable amount of TD is fixed by the same developers who introduced it; this is termed self-fixed TD. This…
A vigorous and growing set of technical debt analysis tools have been developed in recent years -- both research tools and industrial products -- such as Structure 101, SonarQube, and DV8. Each of these tools identifies problematic files…
Technical Debt is a common issue that arises when short-term gains are prioritized over long-term costs, leading to a degradation in the quality of the code. Self-Admitted Technical Debt (SATD) is a specific type of Technical Debt that…
Technical debt is a well-known challenge in software development, and its negative impact on software quality, maintainability, and performance is widely recognized. In recent years, artificial intelligence (AI) has proven to be a promising…
We introduce a data management problem called metadata debt, to identify the mapping between data concepts and their logical representations. We describe how this mapping can be learned using semisupervised topic models based on low-rank…
In the process of software evolution, developers often sacrifice the long-term code quality to satisfy the short-term goals due to specific reasons, which is called technical debt. In particular, self-admitted technical debt (SATD) refers…
Balancing the management of technical debt within recommender systems requires effectively juggling the introduction of new features with the ongoing maintenance and enhancement of the current system. Within the realm of recommender…
Self-admitted technical debt (SATD) is a particular case of Technical Debt (TD) where developers explicitly acknowledge their sub-optimal implementation decisions. Previous studies mine SATD by searching for specific TD-related terms in…
Technical debt denotes shortcuts taken during software development, mostly for the sake of expedience. When such shortcuts are admitted explicitly by developers (e.g., writing a TODO/Fixme comment), they are termed as Self-Admitted…
When developing software, it is vitally important to keep the level of technical debt down since it is well established from several studies that technical debt can, e.g., lower the development productivity, decrease the developers' morale,…
The burgeoning complexity and scale of 3D geometry models pose significant challenges for deployment on resource-constrained platforms. While Post-Training Quantization (PTQ) enables efficient inference without retraining, conventional…
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…
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)…
We consider the problem of tool-to-tool matching (TTTM), also called, chamber matching in the context of a semiconductor manufacturing equipment. Traditional TTTM approaches utilize static configuration data or depend on a golden reference…