Impact of word embedding models on text analytics in deep learning environment: a review
The selection of word embedding and deep learning models for better outcomes is vital.
Word embeddings are an n-dimensional distributed representation of a text that attempts to …
Word embeddings are an n-dimensional distributed representation of a text that attempts to …
Transfer learning with adaptive fine-tuning
With the utilization of deep learning approaches, the key factors for a successful application
are sufficient datasets with reliable ground truth, which are generally not easy to obtain …
are sufficient datasets with reliable ground truth, which are generally not easy to obtain …
Managing technical debt using intelligent techniques-a systematic map** study
Technical Debt (TD) is a metaphor reflecting technical compromises that can yield short-term
benefits but might hurt the long-term health of a software system. With the increasing amount …
benefits but might hurt the long-term health of a software system. With the increasing amount …
Identifying self-admitted technical debt in issue tracking systems using machine learning
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 …
benefits by sacrificing the long-term maintainability and evolvability of software. A special …
Beyond the code: Mining self-admitted technical debt in issue tracker systems
Self-admitted technical debt (SATD) is a particular case of Technical Debt (TD) where
developers explicitly acknowledge their sub-optimal implementation decisions. Previous …
developers explicitly acknowledge their sub-optimal implementation decisions. Previous …
Identifying self-admitted technical debts with jitterbug: A two-step approach
Kee** track of and managing Self-Admitted Technical Debts (SATDs) are important to
maintaining a healthy software project. This requires much time and effort from human …
maintaining a healthy software project. This requires much time and effort from human …
Self-admitted technical debt in the embedded systems industry: An exploratory case study
Technical debt denotes shortcuts taken during software development, mostly for the sake of
expedience. When such shortcuts are admitted explicitly by developers (eg, writing a …
expedience. When such shortcuts are admitted explicitly by developers (eg, writing a …
Detecting and explaining self-admitted technical debts with attention-based neural networks
Self-Admitted Technical Debt (SATD) is a sub-type of technical debt. It is introduced to
represent such technical debts that are intentionally introduced by developers in the process …
represent such technical debts that are intentionally introduced by developers in the process …
Self-admitted technical debt in R: detection and causes
Abstract Self-Admitted Technical Debt (SATD) is primarily studied in Object-Oriented (OO)
languages and traditionally commercial software. However, scientific software coded in …
languages and traditionally commercial software. However, scientific software coded in …
Large language model ChatGPT versus small deep learning models for self‐admitted technical debt detection: Why not together?
Given the increasing complexity and volume of Self‐Admitted Technical Debts (SATDs), how
to efficiently detect them becomes critical in software engineering practice for improving …
to efficiently detect them becomes critical in software engineering practice for improving …