Mining software insights: uncovering the frequently occurring issues in low-rating software applications
In today's digital world, app stores have become an essential part of software distribution,
providing customers with a wide range of applications and opportunities for software …
providing customers with a wide range of applications and opportunities for software …
Automatic software bug prediction using adaptive golden eagle optimizer with deep learning
In the software maintenance and development process, the software bug detection is an
essential problem because it related with the complete software successes. So, the earlier …
essential problem because it related with the complete software successes. So, the earlier …
Buggin: Automatic intrinsic bugs classification model using nlp and ml
P Bhandari, G Rodríguez-Pérez - … Models and Data Analytics in Software …, 2023 - dl.acm.org
Recent studies have shown that bugs can be categorized into in-trinsic and extrinsic types.
Intrinsic bugs can be backtracked to specific changes in the version control system (VCS) …
Intrinsic bugs can be backtracked to specific changes in the version control system (VCS) …
Graph-Driven Exploration of Issue Handling Schemes in Software Projects
B Dobrzyński, J Sosnowski - Applied Sciences, 2024 - mdpi.com
The Issue Tracking System (ITS) repositories are rich sources of software development
documentation that are useful in assessing the status and quality of software projects. An …
documentation that are useful in assessing the status and quality of software projects. An …
Advancing intrinsic and non-intrinsic bug classification with NLP, machine learning, and few-shot prompt engineering
P Bhandari - 2024 - open.library.ubc.ca
Bug classification is a pivotal approach in analyzing bugs, streamlining debugging
processes, and facilitating analysis. Recent studies have shown that bugs can be …
processes, and facilitating analysis. Recent studies have shown that bugs can be …
[PDF][PDF] FSDP: Frequent Software Defects Prediction Based on Defect Correlation Learning for Quality Software Development.
SS Reddy, S Pabboju - International Journal of Intelligent Engineering & …, 2024 - inass.org
Software has become an essential and important part of every domain system. Develo**
quality software is critical to maintaining a stable and secure system. Most of the existing …
quality software is critical to maintaining a stable and secure system. Most of the existing …
Enhancing automated bug report analysis through advanced neural language models
G Long - 2024 - repository.lboro.ac.uk
The recent advances of machine learning, in particular neural language models, has excited
significant growth on a few software engineering research fields. Bug report analysis is one …
significant growth on a few software engineering research fields. Bug report analysis is one …
Predviđanje pogrešaka izvornoga kôda zasnovano na otkrivanju anomalija korištenjem semantičkih značajki izlučenih primjenom autoenkodera na leksičke …
P Afrić - 2023 - dr.nsk.hr
Sažetak Cilj predviđanja pogrešaka u izvornom programskom kôdu je otkrivanje
neispravnih programskih modula kako bi se što bolje alocirali ograničeni resursi za …
neispravnih programskih modula kako bi se što bolje alocirali ograničeni resursi za …
Empirical Deduction and Analysis of Bug Evolution in Deep Learning and Non-Deep Learning Frameworks
TO Ogundare, M Lamothe - Available at SSRN 5139167 - papers.ssrn.com
Deep Learning (DL) frameworks are crucial for develo** deep learning applications but,
like other software, they evolve and can introduce bugs that affect usability and productivity …
like other software, they evolve and can introduce bugs that affect usability and productivity …
Machine Learning and Deep Learning Techniques to Predict Software Defects: A Bibliometric Analysis, Systematic Review, Challenges and Future Works
A Daza Vergaray, OG Apaza Pérez… - … Challenges and Future … - papers.ssrn.com
Abstract In Australia, approximately 66.00% of projects exceeded the programmed budget
and 33% were out of time, all of them due to software failures. The purpose of this study is to …
and 33% were out of time, all of them due to software failures. The purpose of this study is to …