The impact of automated feature selection techniques on the interpretation of defect models
The interpretation of defect models heavily relies on software metrics that are used to
construct them. Prior work often uses feature selection techniques to remove metrics that are …
construct them. Prior work often uses feature selection techniques to remove metrics that are …
Tackling class overlap and imbalance problems in software defect prediction
Software defect prediction (SDP) is a promising solution to save time and cost in the
software testing phase for improving software quality. Numerous machine learning …
software testing phase for improving software quality. Numerous machine learning …
Software defect prediction using stacked denoising autoencoders and two-stage ensemble learning
H Tong, B Liu, S Wang - Information and Software Technology, 2018 - Elsevier
Context Software defect prediction (SDP) plays an important role in allocating testing
resources reasonably, reducing testing costs, and ensuring software quality. However …
resources reasonably, reducing testing costs, and ensuring software quality. However …
Improving defect prediction with deep forest
Context Software defect prediction is important to ensure the quality of software. Nowadays,
many supervised learning techniques have been applied to identify defective instances (eg …
many supervised learning techniques have been applied to identify defective instances (eg …
Bootstrap aggregation ensemble learning-based reliable approach for software defect prediction by using characterized code feature
To ensure software quality, software defect prediction plays a prominent role for the software
developers and practitioners. Software defect prediction can assist us with distinguishing …
developers and practitioners. Software defect prediction can assist us with distinguishing …
An industrial case study of classifier ensembles for locating software defects
As the application layer in embedded systems dominates over the hardware, ensuring
software quality becomes a real challenge. Software testing is the most time-consuming and …
software quality becomes a real challenge. Software testing is the most time-consuming and …
LDFR: Learning deep feature representation for software defect prediction
Abstract Software Defect Prediction (SDP) aims to detect defective modules to enable the
reasonable allocation of testing resources, which is an economically critical activity in …
reasonable allocation of testing resources, which is an economically critical activity in …
[PDF][PDF] Metaheuristic optimization based feature selection for software defect prediction.
Software defect prediction has been an important research topic in the software engineering
field, especially to solve the inefficiency and ineffectiveness of existing industrial approach of …
field, especially to solve the inefficiency and ineffectiveness of existing industrial approach of …
Performance analysis of feature selection methods in software defect prediction: a search method approach
Software Defect Prediction (SDP) models are built using software metrics derived from
software systems. The quality of SDP models depends largely on the quality of software …
software systems. The quality of SDP models depends largely on the quality of software …
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 …