Early detection of earthquakes using iot and cloud infrastructure: A survey
Earthquake early warning systems (EEWS) are crucial for saving lives in earthquake-prone
areas. In this study, we explore the potential of IoT and cloud infrastructure in realizing a …
areas. In this study, we explore the potential of IoT and cloud infrastructure in realizing a …
A survey on large language models: Applications, challenges, limitations, and practical usage
Within the vast expanse of computerized language processing, a revolutionary entity known
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
[HTML][HTML] On the use of deep learning in software defect prediction
Context: Automated software defect prediction (SDP) methods are increasingly applied,
often with the use of machine learning (ML) techniques. Yet, the existing ML-based …
often with the use of machine learning (ML) techniques. Yet, the existing ML-based …
Data quality issues in software fault prediction: a systematic literature review
Software fault prediction (SFP) aims to improve software quality with a possible minimum
cost and time. Various machine learning models have been proposed in the past for …
cost and time. Various machine learning models have been proposed in the past for …
[HTML][HTML] Industrial applications of software defect prediction using machine learning: A business-driven systematic literature review
S Stradowski, L Madeyski - Information and Software Technology, 2023 - Elsevier
Context: Machine learning software defect prediction is a promising field of software
engineering, attracting a great deal of attention from the research community; however, its …
engineering, attracting a great deal of attention from the research community; however, its …
Large language models: a comprehensive survey of its applications, challenges, limitations, and future prospects
Within the vast expanse of computerized language processing, a revolutionary entity known
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
An intuitionistic fuzzy representation based software bug severity prediction approach for imbalanced severity classes
RR Panda, NK Nagwani - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
In order to improve software reliability and quality, the triager must assess the severity of the
software bug and allocate suitable resources on time. However, the triager faces many …
software bug and allocate suitable resources on time. However, the triager faces many …
Machine learning for software engineering: A tertiary study
Machine learning (ML) techniques increase the effectiveness of software engineering (SE)
lifecycle activities. We systematically collected, quality-assessed, summarized, and …
lifecycle activities. We systematically collected, quality-assessed, summarized, and …
A random approximate reduct-based ensemble learning approach and its application in software defect prediction
F Jiang, X Yu, D Gong, J Du - Information Sciences, 2022 - Elsevier
Software defect prediction (SDP) is an important research topic in software engineering. It
can optimize the allocation of testing resources by indicating the defect-prone software …
can optimize the allocation of testing resources by indicating the defect-prone software …
Semantic feature learning for software defect prediction from source code and external knowledge
J Liu, J Ai, M Lu, J Wang, H Shi - Journal of Systems and Software, 2023 - Elsevier
Software defects not only reduce operational reliability but also significantly increase overall
maintenance costs. Consequently, it is necessary to predict software defects at an early …
maintenance costs. Consequently, it is necessary to predict software defects at an early …