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 …
Software fault prediction using data mining, machine learning and deep learning techniques: A systematic literature review
Software fault/defect prediction assists software developers to identify faulty constructs, such
as modules or classes, early in the software development life cycle. There are data mining …
as modules or classes, early in the software development life cycle. There are data mining …
Software vulnerability detection using deep neural networks: a survey
The constantly increasing number of disclosed security vulnerabilities have become an
important concern in the software industry and in the field of cybersecurity, suggesting that …
important concern in the software industry and in the field of cybersecurity, suggesting that …
[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 …
COSTE: Complexity-based OverSampling TEchnique to alleviate the class imbalance problem in software defect prediction
Context: Generally, there are more non-defective instances than defective instances in the
datasets used for software defect prediction (SDP), which is referred to as the class …
datasets used for software defect prediction (SDP), which is referred to as the class …
SLDeep: Statement-level software defect prediction using deep-learning model on static code features
Software defect prediction (SDP) seeks to estimate fault-prone areas of the code to focus
testing activities on more suspicious portions. Consequently, high-quality software is …
testing activities on more suspicious portions. Consequently, high-quality software is …
Software defect prediction employing BiLSTM and BERT-based semantic feature
Recent years, software defect prediction systems are becoming quite popular since they
improve software reliability by identifying the potential bugs in the code. Several models …
improve software reliability by identifying the potential bugs in the code. Several models …
Defect prediction with semantics and context features of codes based on graph representation learning
J Xu, F Wang, J Ai - IEEE Transactions on Reliability, 2020 - ieeexplore.ieee.org
To optimize the process of software testing and to improve software quality and reliability,
many attempts have been made to develop more effective methods for predicting software …
many attempts have been made to develop more effective methods for predicting software …
Graph neural network for source code defect prediction
Predicting defective software modules before testing is a useful operation that ensures that
the time and cost of software testing can be reduced. In recent years, several models have …
the time and cost of software testing can be reduced. In recent years, several models have …
[HTML][HTML] Software fault prediction using an RNN-based deep learning approach and ensemble machine learning techniques
E Borandag - Applied Sciences, 2023 - mdpi.com
Alongside the modern software development life cycle approaches, software testing has
gained more importance and has become an area researched actively within the software …
gained more importance and has become an area researched actively within the software …