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Exploring better alternatives to size metrics for explainable software defect prediction
Delivering reliable software under the constraint of limited time and budget is a significant challenge. Recent progress in software defect...
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LineFlowDP: A Deep Learning-Based Two-Phase Approach for Line-Level Defect Prediction
Software defect prediction plays a key role in guiding resource allocation for software testing. However, previous defect prediction studies still...
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Development of Homogenous Cross-Project Defect Prediction Model Using Artificial Neural Network
Defect prediction is an extremely new software quality assurance study field. A project team’s goal is to provide a high-quality product with no or...
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A comparative study of software defect binomial classification prediction models based on machine learning
As information technology continues to advance, software applications are becoming increasingly critical. However, the growing size and complexity of...
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On the Relevance of Graph2Vec Source Code Embeddings for Software Defect Prediction
Software defects prediction is a crucial activity related to software development and an extensively studied subject that remains challenging. One of...
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Outlier Mining Techniques for Software Defect Prediction
Using software metrics as a method of quantification of software, various approaches were proposed for locating defect-prone source code units within...
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An investigation of online and offline learning models for online Just-in-Time Software Defect Prediction
Just-in-Time Software Defect Prediction (JIT-SDP) operates in an online scenario where additional training data is received over time. Existing...
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Improved Software Fault Prediction Model Based on Optimal Features Set and Threshold Values Using Metaheuristic Approach
Software fault prediction models are very important to prioritize software classes for effective testing and efficient use of resources so that the...
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An extended study on applicability and performance of homogeneous cross-project defect prediction approaches under homogeneous cross-company effort estimation situation
Software effort estimation (SEE) models have been studied for decades. One of serious but typical situations for data-oriented models is the...
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STDPNet: a dual-path surface defect detection neural network based on shearlet transform
Defect detection systems based on machine vision have been widely used as an essential part of intelligent manufacturing systems. However, in...
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Research on Fabric Defect Detection Technology Based on RDN-LTE and Improved DINO
In order to solve the problem of detecting various types of complex fabric defects such as different scale sizes, high fusion with the background and...
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Few-shot defect detection using feature enhancement and image generation for manufacturing quality inspection
Visual defect detection, which is pivotal in industrial quality control, often requires extensive datasets for training deep-learning models....
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YOLO-FDD: efficient defect detection network of aircraft skin fastener
Fasteners defects in aircraft skin can seriously threaten the operational safeness of the aircraft. Therefore, the periodic detection of defects on...
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Visualizations for universal deep-feature representations: survey and taxonomy
In data science and content-based retrieval, we find many domain-specific techniques that employ a data processing pipeline with two fundamental...
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An Empirical Study of Model-Agnostic Interpretation Technique for Just-in-Time Software Defect Prediction
Just-in-time software defect prediction (JIT-SDP) is an effective method of software quality assurance, whose objective is to use machine learning...
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Unsupervised Encoder-Decoder Model for Anomaly Prediction Task
For the anomaly detection task of video sequences, CNN-based methods have been able to learn to describe the normal situation without abnormal...
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Cross project defect prediction: a comprehensive survey with its SWOT analysis
Software fault prediction (SFP) refers to the process of identifying (or predicting) faulty modules based on its characteristics/software metrics....
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Semantic segmentation supervised deep-learning algorithm for welding-defect detection of new energy batteries
As the main component of the new energy battery, the safety vent usually is welded on the battery plate, which can prevent unpredictable explosion...
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Decision Tree Regression Analysis of Proposed Metric Suite for Software Fault Prediction
The objective of this study is to identify a metric suite for software fault prediction that can solve challenges related to reliability, quality,...
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SeqTR: A Simple Yet Universal Network for Visual Grounding
In this paper, we propose a simple yet universal network termed SeqTR for visual grounding tasks, e.g., phrase localization, referring expression...