Advances in machine learning modeling reviewing hybrid and ensemble methods
The conventional machine learning (ML) algorithms are continuously advancing and
evolving at a fast-paced by introducing the novel learning algorithms. ML models are …
evolving at a fast-paced by introducing the novel learning algorithms. ML models are …
Software reliability prediction: A survey
Softwares play an important role in controlling complex systems. Monitoring the proper
functioning of the components of such systems is the principal role of softwares. Often, a …
functioning of the components of such systems is the principal role of softwares. Often, a …
Effective software defect prediction using support vector machines (SVMs)
S Goyal - International Journal of System Assurance Engineering …, 2022 - Springer
Software defect prediction (SDP) plays a key role in the timely delivery of good quality
software product. In the early development phases, it predicts the error-prone modules …
software product. In the early development phases, it predicts the error-prone modules …
A systematic literature review of machine learning applications in software engineering
H Mezouar, AE Afia - International Conference On Big Data and Internet of …, 2022 - Springer
Abstract Machine Learning (ML) has been a concern in Software Engineering (SE) over the
past years. However, how to use ML and what it can offer for SE is still subject to debate …
past years. However, how to use ML and what it can offer for SE is still subject to debate …
A comparative study of statistical and soft computing techniques for reliability prediction of automotive manufacturing
H Soltanali, A Rohani, MH Abbaspour-Fard… - Applied Soft …, 2021 - Elsevier
Reliability and safety analyses are the most important activities for reducing risk of failure
events and upgrading availability of manufacturing industries. The traditional statistical …
events and upgrading availability of manufacturing industries. The traditional statistical …
Online reliability time series prediction via convolutional neural network and long short term memory for service-oriented systems
H Wang, Z Yang, Q Yu, T Hong, X Lin - Knowledge-Based Systems, 2018 - Elsevier
With the development of Web service technology, more and more enterprises choose to
publish their own services on the Internet. However, with the increasing demands of users, it …
publish their own services on the Internet. However, with the increasing demands of users, it …
Enhancing software reliability forecasting through a hybrid ARIMA-ANN model
This paper proposes a hybrid forecasting model combining auto-regressive integrated
moving average (ARIMA) and artificial neural network (ANN) techniques to improve the …
moving average (ARIMA) and artificial neural network (ANN) techniques to improve the …
Towards building a pragmatic cross-project defect prediction model combining non-effort based and effort-based performance measures for a balanced evaluation
Context Recent years have witnessed the growing trend in cross-project defect prediction
(CPDP), where the training and the testing data come from different projects having different …
(CPDP), where the training and the testing data come from different projects having different …
An effective feature selection based cross-project defect prediction model for software quality improvement
Cross-project defect prediction (CPDP) involves the use of other projects (aka source
projects) for training and persuasive model building for a particular project (aka target …
projects) for training and persuasive model building for a particular project (aka target …
Deep-Learning Software Reliability Model Using SRGM as Activation Function
YS Kim, H Pham, IH Chang - Applied Sciences, 2023 - mdpi.com
Software is widely used in various fields. There is no place where it is not used from the
smallest part to the entire part. In particular, the tendency to rely on software is accelerating …
smallest part to the entire part. In particular, the tendency to rely on software is accelerating …