A systematic literature review on software defect prediction using artificial intelligence: Datasets, Data Validation Methods, Approaches, and Tools
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 …
A systematic survey of just-in-time software defect prediction
Recent years have experienced sustained focus in research on software defect prediction
that aims to predict the likelihood of software defects. Moreover, with the increased interest …
that aims to predict the likelihood of software defects. Moreover, with the increased interest …
[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 …
Jitline: A simpler, better, faster, finer-grained just-in-time defect prediction
C Pornprasit… - 2021 IEEE/ACM 18th …, 2021 - ieeexplore.ieee.org
A Just-In-Time (JIT) defect prediction model is a classifier to predict if a commit is defect-
introducing. Recently, CC2Vec-a deep learning approach for Just-In-Time defect prediction …
introducing. Recently, CC2Vec-a deep learning approach for Just-In-Time defect prediction …
A survey on data-driven software vulnerability assessment and prioritization
Software Vulnerabilities (SVs) are increasing in complexity and scale, posing great security
risks to many software systems. Given the limited resources in practice, SV assessment and …
risks to many software systems. Given the limited resources in practice, SV assessment and …
The best of both worlds: integrating semantic features with expert features for defect prediction and localization
To improve software quality, just-in-time defect prediction (JIT-DP)(identifying defect-
inducing commits) and just-in-time defect localization (JIT-DL)(identifying defect-inducing …
inducing commits) and just-in-time defect localization (JIT-DL)(identifying defect-inducing …
The devil is in the tails: How long-tailed code distributions impact large language models
Learning-based techniques, especially advanced Large Language Models (LLMs) for code,
have gained considerable popularity in various software engineering (SE) tasks. However …
have gained considerable popularity in various software engineering (SE) tasks. However …
The impact of data difficulty factors on classification of imbalanced and concept drifting data streams
Class imbalance introduces additional challenges when learning classifiers from concept
drifting data streams. Most existing work focuses on designing new algorithms for dealing …
drifting data streams. Most existing work focuses on designing new algorithms for dealing …
An investigation of cross-project learning in online just-in-time software defect prediction
Just-In-Time Software Defect Prediction (JIT-SDP) is concerned with predicting whether
software changes are defect-inducing or clean based on machine learning classifiers …
software changes are defect-inducing or clean based on machine learning classifiers …
Towards reliable online just-in-time software defect prediction
Throughout its development period, a software project experiences different phases,
comprises modules with different complexities and is touched by many different developers …
comprises modules with different complexities and is touched by many different developers …