Identifying the severity of technical debt issues based on semantic and structural information

Toward prioritization of self-admitted technical debt: an approach to support decision to payment

(2022) Bruno Santos de Lima et al.   SOFTWARE QUALITY JOURNAL

Using BiLSTM with attention mechanism to automatically detect self-admitted technical debt

(2021) Dongjin Yu et al.   Frontiers of Computer Science

Prevalence, common causes and effects of technical debt: Results from a family of surveys with the IT industry

(2021) Robert Ramač et al.   JOURNAL OF SYSTEMS AND SOFTWARE

Multiclass Classification for Self-Admitted Technical Debt Based on XGBoost

(2021) Xin Chen et al.   IEEE TRANSACTIONS ON RELIABILITY

Code smell detection using multi-label classification approach

(2020) Thirupathi Guggulothu et al.   SOFTWARE QUALITY JOURNAL

Wait for it: identifying “On-Hold” self-admitted technical debt

(2020) Rungroj Maipradit et al.   EMPIRICAL SOFTWARE ENGINEERING

Evaluating the agreement among technical debt measurement tools: building an empirical benchmark of technical debt liabilities

(2020) Theodoros Amanatidis et al.   EMPIRICAL SOFTWARE ENGINEERING

Code smell detection and identification in imbalanced environments

(2020) Sofien Boutaib et al.   EXPERT SYSTEMS WITH APPLICATIONS

An Overview and Comparison of Technical Debt Measurement Tools

(2020) Paris C. Avgeriou et al.   IEEE SOFTWARE

Neural Network-based Detection of Self-Admitted Technical Debt

(2019) Xiaoxue Ren et al.   ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY

How developers engage with static analysis tools in different contexts

(2019) Carmine Vassallo et al.   EMPIRICAL SOFTWARE ENGINEERING

Automating Change-level Self-admitted Technical Debt Determination

(2018) Meng Yan et al.   IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

A tertiary study on technical debt: Types, management strategies, research trends, and base information for practitioners

(2018) Nicolli Rios et al.   INFORMATION AND SOFTWARE TECHNOLOGY

SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary

(2018) Alberto Fernandez et al.   JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH

On the value of a prioritization scheme for resolving Self-admitted technical debt

(2018) Solomon Mensah et al.   JOURNAL OF SYSTEMS AND SOFTWARE

Early evaluation of technical debt impact on maintainability

(2018) José M. Conejero et al.   JOURNAL OF SYSTEMS AND SOFTWARE

Using Natural Language Processing to Automatically Detect Self-Admitted Technical Debt

(2017) Everton da Silva Maldonado et al.   IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

Code smell severity classification using machine learning techniques

(2017) Francesca Arcelli Fontana et al.   KNOWLEDGE-BASED SYSTEMS

How do software development teams manage technical debt? – An empirical study

(2016) Jesse Yli-Huumo et al.   JOURNAL OF SYSTEMS AND SOFTWARE

A systematic mapping study on technical debt and its management

(2015) Zengyang Li et al.   JOURNAL OF SYSTEMS AND SOFTWARE

Managing Technical Debt with the SQALE Method

(2012) Jean-Louis Letouzey et al.   IEEE SOFTWARE

Learning from Imbalanced Data

(2009) Haibo He et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Exploratory Undersampling for Class-Imbalance Learning

(2008) Xu-Ying Liu et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS