Software defect prediction using ensemble learning: A systematic literature review
Recent advances in the domain of software defect prediction (SDP) include the integration of
multiple classification techniques to create an ensemble or hybrid approach. This technique …
multiple classification techniques to create an ensemble or hybrid approach. This technique …
A systematic literature review on software defect prediction using artificial intelligence: Datasets, Data Validation Methods, Approaches, and Tools
J Pachouly, S Ahirrao, K Kotecha… - … Applications of Artificial …, 2022 - Elsevier
Delivering high-quality software products is a challenging task. It needs proper coordination
from various teams in planning, execution, and testing. Many software products have high …
from various teams in planning, execution, and testing. Many software products have high …
Handling class-imbalance with KNN (neighbourhood) under-sampling for software defect prediction
S Goyal - Artificial Intelligence Review, 2022 - Springer
Abstract Software Defect Prediction (SDP) is highly crucial task in software development
process to forecast about which modules are more prone to errors and faults before the …
process to forecast about which modules are more prone to errors and faults before the …
Heterogeneous defect prediction
Software defect prediction is one of the most active research areas in software engineering.
We can build a prediction model with defect data collected from a software project and …
We can build a prediction model with defect data collected from a software project and …
A survey on machine learning techniques for source code analysis
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …
these techniques to a myriad of software engineering tasks that use source code analysis …
Progress on approaches to software defect prediction
Software defect prediction is one of the most popular research topics in software
engineering. It aims to predict defect‐prone software modules before defects are discovered …
engineering. It aims to predict defect‐prone software modules before defects are discovered …
Deep just-in-time defect prediction: how far are we?
Defect prediction aims to automatically identify potential defective code with minimal human
intervention and has been widely studied in the literature. Just-in-Time (JIT) defect prediction …
intervention and has been widely studied in the literature. Just-in-Time (JIT) defect prediction …
TLEL: A two-layer ensemble learning approach for just-in-time defect prediction
Context Defect prediction is a very meaningful topic, particularly at change-level. Change-
level defect prediction, which is also referred as just-in-time defect prediction, could not only …
level defect prediction, which is also referred as just-in-time defect prediction, could not only …
An empirical study of model-agnostic techniques for defect prediction models
J Jiarpakdee, CK Tantithamthavorn… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Software analytics have empowered software organisations to support a wide range of
improved decision-making and policy-making. However, such predictions made by software …
improved decision-making and policy-making. However, such predictions made by software …
Software defect prediction based on kernel PCA and weighted extreme learning machine
Context Software defect prediction strives to detect defect-prone software modules by mining
the historical data. Effective prediction enables reasonable testing resource allocation …
the historical data. Effective prediction enables reasonable testing resource allocation …