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The Effect of the Dataset Size on the Accuracy of Software Defect Prediction Models: An Empirical Study
2021
Inteligencia Artificial
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Software defect prediction models are crucial for software quality assurance. This study investigates the impact of dataset size and feature selection algorithms on software defect prediction models. ...
We found that applying the SVM defect prediction model on datasets with a reduced number of measures as features may enhance the accuracy of the fault prediction model. ...
Alshammari would like to acknowledge the support of University of Ha'il and M. Alshayeb acknowledges the support of King Fahd University of Petroleum & Minerals. ...
doi:10.4114/intartif.vol24iss68pp72-88
doaj:8437f3a053d44ca8bd13389c3929b4b3
fatcat:h36osgkrlnaj5inupey4y3oz2m
Threshold benchmarking for feature ranking techniques
2021
Bulletin of Electrical Engineering and Informatics
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In this work, an empirical study is conducted for identification of the threshold benchmark for feature ranking algorithms. ...
In prediction modeling, the choice of features chosen from the original feature set is crucial for accuracy and model interpretability. ...
On empirical grounds, previous works [6, 7] , have proposed log2(N) to be the number of selected features for defect prediction models, where N is the total number of features in the metric space. ...
doi:10.11591/eei.v10i2.2752
fatcat:uleibvjkxzaplmzi2ieilzmnfe
An Empirical Assessment and Validation of Redundancy Metrics Using Defect Density as Reliability Indicator
2021
Scientific Programming
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Therefore, a linear regression technique is used to show the usefulness of these metrics as significant indicators of software defect density. ...
Literature review shows a lack of software metrics which are proposed for reliability measurement and prediction. ...
basic idea is to exploit the generated database to study the relationship between the metrics and defect density using regression techniques [8, 28, 40] . erefore, we propose in Section 3 an empirical ...
doi:10.1155/2021/8325417
fatcat:l4u45zvauvh3bkb4dogupzfz7q
Investigating Implications of Metric Based Predictive Data Mining Approaches towards Software Fault Predictions
2018
International Journal of Engineering & Technology
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These studies are gathered from a pool of total 587 manuscripts. The selection criteria for these manuscripts are title, keywords and citation of that paper. ...
Objective: In this research work, author's major objective is to investigate the context and dimensions of research studies performed by different researchers in the area of software fault prediction. ...
It included those studies that empirically compared the software metrics for software fault prediction. ...
doi:10.14419/ijet.v7i3.12.16122
fatcat:cbnkzf5tzfbonmx3bbkp755mxm
An empirical study on predicting defect numbers
2015
Proceedings of the 27th International Conference on Software Engineering and Knowledge Engineering
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Many methods have been proposed to predict the defect-proneness of software components using supervised classification techniques in within-and cross-project scenarios. ...
Defect prediction is an important activity to make software testing processes more targeted and efficient. ...
distribution of defects in a given software project, and (2) selecting the most suitable training data for defect numbers prediction using transfer learning techniques [31] in the scenario of CPDP. ...
doi:10.18293/seke2015-132
dblp:conf/seke/ChenM15
fatcat:6mvnp3mt2zhjdfw3wmsimhvomi
Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review
2021
International Journal of Advanced Computer Science and Applications
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Defect detection in software is the procedure to identify parts of software that may comprise defects. ...
Therefore, these companies need to build an intelligent model capable of detecting software defects accurately and efficiently. The paper is organized as follows. ...
IV STUDIES OF SOFTWARE DEFECTS PREDICTION a techniques various kernel Sigmoid kernel). model for predicting defects in software projects on the An empirical model for fault prediction on the basis of regression ...
doi:10.14569/ijacsa.2021.0121128
fatcat:4q3f7v2uwbgozmrzbwjnp4snja
Predicting Software Defects through SVM: An Empirical Approach
[article]
2018
arXiv
pre-print
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Software defect prediction is an important aspect of preventive maintenance of a software. Many techniques have been employed to improve software quality through defect prediction. ...
The results signify the role of smells in predicting the defects of a software. The results can further be used as a baseline to investigate further the role of smells in predicting defects. ...
Software defect prediction is the application of different techniques to predict possible defects in a software. ...
arXiv:1803.03220v1
fatcat:tmeoxwiog5aydccxoksy6k4l54
Progress on Machine Learning Techniques for Software Fault Prediction
2019
International Journal of Advanced Trends in Computer Science and Engineering
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Software fault prediction is a significant part of software engineering. Fault prediction means to identify fault prone modules at the early stage of software development. ...
This paper also discusses the substantial research performed in software fault prediction using machine learning techniques. ...
Ezgi et al. (2016) proposed an iterative software defect prediction model that uses fuzzy inference system The result shows that it is a successful technique and it becomes an automated tool to locate ...
doi:10.30534/ijatcse/2019/33822019
fatcat:akql63chkzgzhm5azngmceh45i
Choosing software metrics for defect prediction: an investigation on feature selection techniques
2011
Software, Practice & Experience
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The selection of software metrics for building software quality prediction models is a search-based software engineering problem. ...
The case study is based on software metrics and defect data collected from multiple releases of a large real-world software system. ...
We also extend our appreciation to the guest editors, Drs Simon Poulding and Iain Bate, of this special issue, and to the anonymous reviewers for their insightful comments. ...
doi:10.1002/spe.1043
fatcat:zyeogaoocraxti4ad3ghrl4dla
Effective Prediction of Software Defects using Random-tree Entropy based Feature Selection Framework
2022
International Journal of Advanced Computer Science and Applications
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Thus, in this study, a novel approach is proposed for predicting the number of software defects based on relevant variables using ML. ...
And finally, the software defect dataset of National Aeronautics and Space Administration (NASA) PC-1 is sent to an ML-based model to estimate the number of faults. ...
Our study used 30-repetition holdout and 10-fold cross-validation. An improved CNN model was then proposed and compared to previous CNN findings and an empirical study. ...
doi:10.14569/ijacsa.2022.0130541
fatcat:5bjrn2m57rdx7am4dpffdbm7u4
Software Defect Prediction Using Stacking Generalization of Optimized Tree-Based Ensembles
2022
Applied Sciences
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Software defect prediction refers to the automatic identification of defective parts of software through machine learning techniques. ...
In this paper, we investigate the applicability of a stacking ensemble built with fine-tuned tree-based ensembles for defect prediction. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app12094577
fatcat:j7war5ytfnas5gyrp4ldi43tsm
Impact of Feature Selection Methods on the Predictive Performance of Software Defect Prediction Models: An Extensive Empirical Study
2020
Symmetry
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Feature selection (FS) is a feasible solution for mitigating high dimensionality problem, and many FS methods have been proposed in the context of software defect prediction (SDP). ...
It is hence critical to conduct an extensive empirical study to address these contradictions to guide researchers and buttress the scientific tenacity of experimental conclusions. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/sym12071147
fatcat:dqno3hw6k5dpppte2rrdta5zki
An empirical study on software defect prediction with a simplified metric set
2015
Information and Software Technology
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Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2014 pre-print arXiv:1402.3873v3 fatcat:xn2auzbbr5h65clq5ippq2jvziOther Versions
Software defect prediction plays a crucial role in estimating the most defect-prone components of software, and a large number of studies have pursued improving prediction accuracy within a project or ...
The objective of this work is to validate the feasibility of the predictor built with a simplified metric set for software defect prediction in different scenarios, and to investigate practical guidelines ...
Acknowledgment We greatly appreciate the constructive comments and useful suggestions from the editor and anonymous reviewers, which help us improve the quality and readability of our paper. ...
doi:10.1016/j.infsof.2014.11.006
fatcat:wq6dgwcnjnantn5it62zvyltfa
Assessing Software Defect Prediction on WLCG Software: a Study with Unlabelled Datasets and Machine Learning Techniques
2019
Zenodo
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features (i.e. software metrics) for the various software modules (such as files, classes and functions) but lack of modules classification like their defectiveness. ...
This study also includes new approaches to label the various modules due to the heterogeneity of software metrics distribution. ...
Robbes, Evaluating defect prediction approaches: a benchmark and an
extensive comparison, Empirical software Engineering, vol. 17, no. 4{5, pp. 531{577,2012. ...
doi:10.5281/zenodo.3599450
fatcat:hwk5zdnpfrfo3k3vo5ufgtzvxe
An empirical study of just-in-time defect prediction using cross-project models
2014
Proceedings of the 11th Working Conference on Mining Software Repositories - MSR 2014
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However, cross-project models have not yet been explored in the context of JIT prediction. Therefore, in this study, we empirically evaluate the performance of JIT cross-project models. ...
Prior research suggests that predicting defect-inducing changes, i.e., Just-In-Time (JIT) defect prediction is a more practical alternative to traditional defect prediction techniques, providing immediate ...
We, therefore, set out to empirically study the performance of JIT cross-project defect models. ...
doi:10.1145/2597073.2597075
dblp:conf/msr/FukushimaKMYU14
fatcat:557zxvnxdjdlrcqqtakzqczun4
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