On the assessment of software defect prediction models via ROC curves
Sign Up to like & getrecommendations! Published in 2020 at "Empirical Software Engineering"
DOI: 10.1007/s10664-020-09861-4
Abstract: Software defect prediction models are classifiers often built by setting a threshold t on a defect proneness model, i.e., a scoring function. For instance, they classify a software module non-faulty if its defect proneness is… read more here.
Keywords: defect prediction; defect proneness; performance; defect ... See more keywords
Imbalanced Data Processing Model for Software Defect Prediction
Sign Up to like & getrecommendations! Published in 2018 at "Wireless Personal Communications"
DOI: 10.1007/s11277-017-5117-z
Abstract: In the field of software engineering, software defect prediction is the hotspot of the researches which can effectively guarantee the quality during software development. However, the problem of class imbalanced datasets will affect the accuracy… read more here.
Keywords: imbalanced data; defect prediction; model; software defect ... See more keywords
Optimization of association rules using hybrid data mining technique
Sign Up to like & getrecommendations! Published in 2021 at "Innovations in Systems and Software Engineering"
DOI: 10.1007/s11334-021-00387-6
Abstract: Software quality has been the important area of interest for decades now in the IT sector and software firms. Defect prediction gives the tester the pointers as to where the bugs will most likely be… read more here.
Keywords: data mining; hybrid data; software; mining technique ... See more keywords
A Cluster Based Feature Selection Method for Cross-Project Software Defect Prediction
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Computer Science and Technology"
DOI: 10.1007/s11390-017-1785-0
Abstract: Cross-project defect prediction (CPDP) uses the labeled data from external source software projects to compensate the shortage of useful data in the target project, in order to build a meaningful classification model. However, the distribution… read more here.
Keywords: defect prediction; selection; feature selection; software ... See more keywords
A Framework for Software Defect Prediction and Metric Selection
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2017.2785445
Abstract: Automated software defect prediction is an important and fundamental activity in the domain of software development. However, modern software systems are inherently large and complex with numerous correlated metrics that capture different aspects of the… read more here.
Keywords: defect prediction; software defect; metric selection; prediction ... See more keywords
An Ensemble Oversampling Model for Class Imbalance Problem in Software Defect Prediction
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2817572
Abstract: Software systems are now ubiquitous and are used every day for automation purposes in personal and enterprise applications; they are also essential to many safety-critical and mission-critical systems, e.g., air traffic control systems, autonomous cars,… read more here.
Keywords: defect prediction; faulty components; model; class imbalance ... See more keywords
An Empirical Study on the Effectiveness of Feature Selection for Cross-Project Defect Prediction
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2895614
Abstract: Software defect prediction has attracted much attention of researchers in software engineering. At present, feature selection approaches have been introduced into software defect prediction, which can improve the performance of traditional defect prediction (known as… read more here.
Keywords: defect prediction; project defect; feature selection; feature ... See more keywords
Seml: A Semantic LSTM Model for Software Defect Prediction
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2925313
Abstract: Software defect prediction can assist developers in finding potential bugs and reducing maintenance cost. Traditional approaches usually utilize software metrics (Lines of Code, Cyclomatic Complexity, etc.) as features to build classifiers and identify defective software… read more here.
Keywords: defect prediction; lstm model; prediction; software defect ... See more keywords
Few-Shot Learning Based Balanced Distribution Adaptation for Heterogeneous Defect Prediction
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2973924
Abstract: Heterogeneous defect prediction (HDP) aims to predict the defect tendency of modules in one project using heterogeneous data collected from other projects. It sufficiently incorporates the two characteristics of the defect prediction data: (1) datasets… read more here.
Keywords: balanced distribution; distribution adaptation; prediction; defect prediction ... See more keywords
Adversarial Learning for Cross-Project Semi-Supervised Defect Prediction
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2974527
Abstract: Cross-project defect prediction (CPDP) aims to build a prediction model on existing source projects and predict the labels of target project. The data distribution difference between different projects makes CPDP very challenging. Besides, most existing… read more here.
Keywords: project semi; project; prediction; cross project ... See more keywords
Graph Neural Network for Source Code Defect Prediction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3144598
Abstract: 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 been proposed for this purpose, most… read more here.
Keywords: source code; defect prediction; source; code ... See more keywords