Mining software insights: uncovering the frequently occurring issues in low-rating software applications

ND Khan, JA Khan, J Li, T Ullah, Q Zhao - PeerJ Computer Science, 2024 - peerj.com
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 …

Automatic software bug prediction using adaptive golden eagle optimizer with deep learning

R Siva, KS, B Hariharan, N Premkumar - Multimedia Tools and …, 2024 - Springer
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 …

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) …

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 …

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 …

[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 …

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 …

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 …

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 …

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 …